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To Power A.I., Start-Up Creates a Giant Computer Chip -
Aug. 19, 2019 The New York Times By Cade Metz.

New A.I. systems rely on neural networks. Loosely based on the network of neurons in the human brain, these complex mathematical systems can learn tasks by analyzing vast amounts of data. By pinpointing patterns in thousands of cat photos, for instance, a neural network can learn to recognize a cat.

That requires a particular kind of computing power. Today, most companies analyze data with help from graphics processing units, or G.P.U.s. These chips were originally designed to render images for games and other software, but they are also good at running the math that drives a neural network.

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About six years ago, as tech giants like Google, Facebook and Microsoft doubled down on artificial intelligence, they started buying enormous numbers of G.P.U.s from the Silicon Valley chip maker Nvidia. In the year leading up to the summer of 2016, Nvidia sold $143 million in G.P.U.s. That was more than double the year before.

But the companies wanted even more processing power. Google built a chip specifically for neural networks — the tensor processing unit, or T.P.U. — and several other chip makers chased the same goal.
artificial_intelligence  Cerebras  conventional_wisdom  Intel  Qualcomm  semiconductors  start_ups 
18 days ago by jerryking
Looking Ahead After a Quarter Century Into the Digital Age - CIO Journal
Aug 16, 2019 | WSJ | By Irving Wladawsky-Berger.

* Large economic potential is linked to digitization—and much of it is yet to be captured
* Digital superstars are rising far beyond the U.S. big four and China’s big three
* Digital natives are calling the shots
* Digital changes everything—even industry boundaries
* Agile is the new way to compete
* Playing the platform economy can boost earnings
* Self-cannibalization and innovation are a necessity for digital reinvention
* Going after the right M&A is key
* Effective management of digital transformation is vital—but challenging
* Leveraging and transitioning from digital to new frontier technologies is an imperative


Effective management of digital transformation is vital—but challenging. High incidences of failure can be found across industries and countries regardless of the objectives of the digital transformation, including customer experience, the most common type of transformation.

The report recommends five key actions to improve the odds of a successful digital transformation: shared responsibility and accountability; clarity of objectives and commitment; sufficient resources; investments in digital talent; and flexibility and agility.
artificial_intelligence  digital_economy  industry_boundaries  insights  Irving_Wladawsky-Berger  McKinsey  M&A  millennials  platforms  self-cannibalization 
26 days ago by jerryking
Opinion: Canadian companies must prepare for disruptors to come knocking
July 26, 2019 | The Globe and Mail | by JOHN RUFFOLO.

In August, 2011, technology legend Marc Andreessen wrote his seminal article titled Why Software Is Eating the World, which became the central investment thesis behind his venture capital firm Andreessen Horowitz. Andreessen’s prognostication has since followed Amara’s Law on the effect of technology, which aptly states: “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” The feast has really just begun.

We are in the midst of the Fourth Industrial Revolution – or as some call it, the Information Revolution.....the Information Revolution really began to take shape in 2008, catalyzed by three incredibly powerful and converging forces – mobility-first, cloud computing and social media. All three forces collided together with full impact in 2008, spawning a wave of new technology companies.......The next phase of the Fourth Industrial Revolution will see the rise of a new species of company – the “disruptors.” While technology companies will continue to grow, we are witnessing the enablement of those technologies across all economic sectors as the leading weapon used by new entrants to disrupt the traditional incumbents in their respective industries. The massive influx of venture capital to support the building and growth of technology companies over the past 10 years has produced these tools, such as artificial intelligence, machine learning, and the internet of things, which are now being leveraged across all industries......Those companies that can harness these new technologies to operate better and faster, and to gain unmatched insights into their customers, will prosper. Although these disruptors are not technology companies in the conventional sense, their tight focus on value creation through innovation further blurs the lines between a technology company and a traditional company.

The incumbents, however, are not asleep at the wheel. To ward off the disruptors, they know they must embrace technology. It is this battleground that I believe will generate the greatest wealth creation and transfer opportunities over the next decade. The disruptors, naturally, are particularly active in those industries where they perceive the incumbents to be burdened by outdated technological infrastructure or business models, and hard-pressed to counterattack.

Yesterday, the disruptors focused primarily on consumer sectors such as the music industry, travel booking, newspapers, magazines and book publishing. Today, it’s groceries, entertainment and personal transportation, thanks to Amazon, Netflix and Uber, respectively.

But consumer-focused sectors were just the start for the disruptors. Before long, I believe we will see them try to disrupt varied industries such as banking, insurance, health care, real estate and even agriculture and mining; no industry will be immune. These sectors all represent emblematic Canadian brands, and yes, each will in turn will go through the same jarring disruption as so many others.
************************************************
See [Why It’s Not Enough Just to Be Disruptive - The New York Times
By JEREMY G. PHILIPS AUG. 10, 2016] Creating enormous value over the long term requires turning a tactical edge into some form of durable advantage....Superior tactical execution can still create real value, particularly where it provides ammunition for a bigger war (like Walmart’s battle with Amazon). And in the long term, value is created not by disruption, but by weaving together advantages (as both Amazon and Walmart have done in different ways) that together create a barrier that is hard to storm.
Amara's_Law  artificial_intelligence  cloud_computing  digital_savvy  disruption  incumbents  investment_thesis  John_Ruffolo  legacy_tech  Marc_Andreessen  mobility_first  overestimation  social_media  software_is_eating_the_world  start_ups  technology  underestimation  venture_capital 
7 weeks ago by jerryking
Canada’s AI Ecosystem — Toronto - Believing - Medium
Aug 8, 2018
Part 2: Ontario’s complete artificial intelligence value chain
artificial_intelligence  Canada  ecosystems  Ontario  value_chains 
9 weeks ago by jerryking
What will Apple do without Jony Ive?
June 27, 2019 | Financial Times | by Tim Bradshaw, Global Technology Correspondent.

Sir Jonathan prepares to move on from Apple to launch his own new venture, LoveFrom, after more than two decades at the Silicon Valley giant.....As a company worth nearly $1tn, Apple today is financially secure. But Sir Jonathan's looming departure will once again raise questions about its future. 

This is not the first time that Sir Jonathan’s role has evolved. In recent years, his design expertise has extended beyond crafting Apple’s pocketable devices. He helped retail chief Angela Ahrendts overhaul its stores, from fixtures such as its tree-lined “Genius Groves”, down to simplifying product packaging. 

More significantly, he oversaw the company’s long-planned move to its new headquarters, Apple Park, which was first conceived with Jobs back in 2004 and designed in partnership with British architects Foster + Partners.....Speaking at a Wired magazine event in 2018, he appeared to suggest that he was back for the long haul, saying: “There’s an awful lot to do and an awful lot of opportunity.” ....Apple Park...brought Apple’s entire design team together for the first time into one purpose-built studio, with industrial designers sitting side by side with font and interface designers......Perhaps the most important legacy that Jon Ive leaves . . . is the team.”.......By Apple’s outsized standards, the tight-knit group of people who work on product design is small. It runs to just a few dozen people out of an organisation that employs some 132,000 staff.....
Yet the team wields a disproportionate influence inside the Cupertino-based company. With an extensive array of tooling and fabrication equipment that is rarely found outside a manufacturing plant, the studio explores new product categories and the materials that might build them, from unique blends of aluminium to ceramics. 

They define not only a product’s appearance but how its software looks and feels, how it responds to gestures, even how an iPhone or Watch gently vibrates to give a user “haptic feedback”. 

“No group within Apple has more power than the industrial designers,” ......Jonathan Ive has thousands of patents to his name, encompassing the original iPod and iPhone to more obscure innovations, including the iPad’s magnetic cover, the Apple Store’s wooden tables and a lanyard used to attach an iPod to a wrist......Jonathan’s departure is likely to reopen a debate that has been simmering for several years — namely how will Apple come up with a new hit product that can match the unprecedented success of the iPhone, whose record-breaking profits propelled Apple to become the first trillion-dollar company last year........it may be that no single product ever will top the iPhone — for any tech company, not just Apple. It is a question that hangs over Silicon Valley as the industry casts around for a new platform, be it virtual reality or smart speakers, that might become as ubiquitous and essential as the smartphone.........Apple is also putting greater attention on an expanding portfolio of online services, including games, news and video........Tim Cook and Jonathan Ive have both pointed to healthcare as a potential new market for Apple, building on the Watch’s new capabilities for detecting heart irregularities.....Healthcare is just one example of how the battleground has changed for Apple in recent years. Despite pioneering virtual assistants with Siri, Apple found itself outflanked by Amazon’s Alexa and Google Assistant in both sales of smart speakers and artificial intelligence capabilities.

New blood at Apple

Some analysts believe that new blood could invigorate Apple’s response to these challenges. Alongside the high-profile departures of Ms Ahrendts and Sir Jonathan, Apple poached John Giannandrea from Google to become its head of machine learning and AI strategy, as well as Hollywood veterans Jamie Erlicht and Zack Van Amberg from Sony Pictures Television to run its push into original video. 

“The apparent acceleration in the pace of change within Apple at the executive level reflects the paradigm shift the company is undergoing from a hardware-driven story to ‘Apple as a service’,....... the most significant concern for investors will be that Sir Jonathan’s departure will take away another arbiter of focus and product direction that Apple had already lost with the death of Jobs.....Jonathan’s focus is growing beyond the steel and glass borders of Apple Park, saying he wants to “solve some complicated problems”. .....“One defining characteristics is almost a fanatical curiosity,” he said. “But if you don’t have the space, if you don’t have the tools and the infrastructure, that curiosity can often not have the opportunity to be pursued.”

LoveFrom itself defies traditional categorisation. “I have no interest in creating yet another design agency,” he said firmly. “What’s important is the values and what motivates that collection of people …Small groups of people, I think as Apple has demonstrated over the years, can do some extraordinary things.”

 

 

 
Alexa  Apple  Apple_IDs  Apple_Park  artificial_intelligence  breakthroughs  curiosity  design  departures  exits  Google_Assistant  haptics  healthcare  Jonathan_Ive  LoveFrom  new_categories  new_products  patents  services  Silicon_Valley  Siri  smart_speakers  subscriptions  teams  Tim_Cook  virtual_assistants 
11 weeks ago by jerryking
Opinion | How Artificial Intelligence Can Save Your Life
June 24, 2019 | The New York Times | By David Brooks.
Opinion Columnist

In his book “Deep Medicine,” which is about how A.I. is changing medicine across all fields, Eric Topol describes a study in which a learning algorithm was given medical records to predict who was likely to attempt suicide. It accurately predicted attempts nearly 80 percent of the time. By incorporating data of real-world interactions such as laughter and anger, an algorithm in a similar study was able to reach 93 percent accuracy.....
algorithms  artificial_intelligence  books  David_Brooks  depression  diagnostic  doctors  medical  mens'_health  mental_health  op-ed  pattern_recognition  predictive_analytics  tools  visual_cues 
11 weeks ago by jerryking
Data Challenges Are Halting AI Projects, IBM Executive Says
May 28, 2019 | WSJ | By Jared Council.

About 80% of the work with an AI project is collecting and preparing data. Some companies aren’t prepared for the cost and work associated with that going in,......“And so you run out of patience along the way, because you spend your first year just collecting and cleansing the data,”.....“And you say: ‘Hey, wait a moment, where’s the AI? I’m not getting the benefit.’ And you kind of bail on it.”....A report this month by Forrester Research Inc. found that data quality is among the biggest AI project challenges. Forrester analyst Michele Goetz said companies pursuing such projects generally lack an expert understanding of what data is needed for machine-learning models and struggle with preparing data in a way that’s beneficial to those systems.

She said producing high-quality data involves more than just reformatting or correcting errors: Data needs to be labeled to be able to provide an explanation when questions are raised about the decisions machines make.

While AI failures aren’t much talked about, Ms. Goetz said companies should be prepared for them and use them as teachable moments. “Rather than looking at it as a failure, be mindful about, ‘What did you learn from this?’”
artificial_intelligence  data_collection  data_quality  data_wrangling  IBM  IBM_Watson  teachable_moments 
may 2019 by jerryking
An equation to ensure America survives the age of AI
April 10, 2019 | Financial Times | Elizabeth Cobbs.

Alexander Hamilton, Horace Mann and Frances Perkins are linked by their emphasis on the importance of human learning.

In more and more industries, the low-skilled suffer declining pay and hours. McKinsey estimates that 60 per cent of occupations are at risk of partial or total automation. Workers spy disaster. Whether the middle class shrinks in the age of artificial intelligence depends less on machine learning than on human learning. Historical precedents help, especially...... the Hamilton-Mann-Perkins equation: innovation plus education, plus a social safety net, equals the sum of prosperity.

(1) Alexander Hamilton.
US founding father Alexander Hamilton was first to understand the relationship between: (a) the US's founding coincided with the industrial revolution and the need to grapple with technological disruption (In 1776, James Watts sold his first steam engine when the ink was still wet on the Declaration of Independence)-- Steam remade the world economically; and (b), America’s decolonisation remade the world politically......Hamilton believed that Fledgling countries needed robust economies. New technologies gave them an edge. Hamilton noted that England owed its progress to the mechanization of textile production.......Thomas Jefferson,on the other hand, argued that the US should remain pastoral: a free, virtuous nation exchanged raw materials for foreign goods. Farmers were “the chosen people”; factories promoted dependence and vice.....Hamilton disagreed. He thought colonies shouldn’t overpay foreigners for things they could produce themselves. Government should incentivise innovation, said his 1791 Report on the Subject of Manufactures. Otherwise citizens would resist change even when jobs ceased to provide sufficient income, deterred from making a “spontaneous transition to new pursuits”.......the U.S. Constitution empowered Congress to grant patents to anyone with a qualified application. America became a nation of tinkerers...Cyrus McCormick, son of a farmer, patented a mechanical reaper in 1834 that reduced the hands needed in farming. The US soared to become the world’s largest economy by 1890. Hamilton’s constant: nurture innovation.

(2) Horace Mann
America’s success gave rise to the idea that a free country needed free schools. The reformer Horace Mann, who never had more than six weeks of schooling in a year, started the Common School Movement, calling public schools “the greatest discovery made by man”.....Grammar schools spread across the US between the 1830s and 1880s. Reading, writing and arithmetic were the tools for success in industrialising economies. Towns offered children a no-cost education.......Americans achieved the world’s highest per capita income just as they became the world’s best-educated people. Mann’s constant: prioritise education.

(3) Frances Perkins
Jefferson was correct that industrial economies made people more interdependent. By 1920, more Americans lived in towns earning wages than on farms growing their own food. When the Great Depression drove unemployment to 25 per cent, the state took a third role....FDR recruited Frances Perkins, the longest serving labour secretary in US history, to rescue workers. Perkins led campaigns that established a minimum wage and maximum workweek. Most importantly, she chaired the committee that wrote the 1935 Social Security Act, creating a federal pension system and state unemployment insurance. Her achievements did not end the depression, but helped democracy weather it. Perkins’s constant: knit a safety net.

The world has ridden three swells of industrialisation occasioned by the harnessing of steam, electricity and computers. The next wave, brought to us by AI, towers over us. History shows that innovation, education and safety nets point the ship of state into the wave.

Progress is a variable. Hamilton, Mann and Perkins would each urge us to mind the constants in the historical equation.
adaptability  Alexander_Hamilton  artificial_intelligence  automation  diadaptability  constitutions  disruption  downward_mobility  education  FDR  Founding_Fathers  Frances_Perkins  gig_economy  historical_precedents  hollowing_out  Horace_Mann  Industrial_Revolution  innovation  innovation_policies  James_Watts  job_destruction  job_displacement  job_loss  life_long_learning  low-skilled  McKinsey  middle_class  priorities  productivity  public_education  public_schools  safety_nets  slavery  steam_engine  the_Great_Depression  Thomas_Jefferson  tinkerers 
april 2019 by jerryking
DE Shaw: inside Manhattan’s ‘Silicon Valley’ hedge fund
March 25, 2019 | Financial Times Robin Wigglesworth in New York.

for a wider investment industry desperately trying to reinvent itself for the 21st century, DE Shaw has evolved dramatically from the algorithmic, computer-driven “quantitative” trading it helped pioneer in the 1980s.

It is now a leader in combining quantitative investing with traditional “fundamental” strategies driven by humans, such as stockpicking. This symbiosis has been dubbed “quantamental” by asset managers now attempting to do the same. Many in the industry believe this is the future, and are rushing to hire computer scientists to help realise the benefits of big data and artificial intelligence in their strategies........DE Shaw runs some quant strategies so complex or quick that they are in practice almost beyond human understanding — something that many quantitative analysts are reluctant to concede.

The goal is to find patterns on the fuzzy edge of observability in financial markets, so faint that they haven’t already been exploited by other quants. They then hoard as many of these signals as possible and systematically mine them until they run dry — and repeat the process. These can range from tiny, fleeting arbitrage opportunities between closely-linked stocks that only machines can detect, to using new alternative data sets such as satellite imagery and mobile phone data to get a better understanding of a company’s results...... DE Shaw is also ramping up its investment in the bleeding edge of computer science, setting up a machine learning research group led by Pedro Domingos, a professor of computer science and engineering and author of The Master Algorithm, and investing in a quantum computing start-up.

It is early days, but Cedo Crnkovic, a managing director at DE Shaw, says a fully-functioning quantum computer could potentially prove revolutionary. “Computing power drives everything, and sets a limit to what we can do, so exponentially more computing power would be transformative,” he says.
algorithms  alternative_data  artificial_intelligence  books  D.E._Shaw  financial_markets  hedge_funds  investment_management  Manhattan  New_York_City  quantitative  quantum_computing  systematic_approaches 
march 2019 by jerryking
How to Navigate Investing in A.I., From Someone Who’s Done It
March 2, 2019 | The New York Times | By Katie Robertson.

Reid Hoffman, the co-founder of LinkedIn and a prominent venture capitalist, said at The New York Times’s New Work Summit in California that he looked very carefully at A.I. ventures to see how they were making new, interesting things possible and how he could bet on them early. He said current machine learning techniques, which are transforming fundamental industries, gave an amazing glimpse of the future.

“My ideal investing is stuff that looks a little crazy now and in three years is obvious or five years is obvious,” Mr. Hoffman said.....voiced some concerns around how A.I. could transform the global landscape, likening it to the shift from the agricultural age to the industrial age.

“You’ll see enormous changes from where the bulk of people find jobs and employment,” he said. “The first worry is what does that transition look like. That intervening transition is super painful.”....Mr. Hoffman recently released the book “Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies,” which details his theory that the rapid growth of a company — above almost all else — is what leads to its success.
artificial_intelligence  blitzscaling  books  competitive_landscape  machine_learning  Reid_Hoffman  scaling  Silicon_Valley  start_ups  vc  venture_capital 
march 2019 by jerryking
Citigroup CEO says machines could cut thousands of call centre jobs
February 17, 2019 | Financial Times | Laura Noonan and Patrick Jenkins in Dublin.

Citigroup chief executive Mike Corbat has suggested that “tens of thousands” of people working in the US bank’s call centres are likely to be replaced by machines that can “radically change or improve” customers’ experience while cutting costs.

Mr Corbat, who runs America’s fourth-largest bank by assets, made the comments in an interview with the Financial Times in which he also ruled out Citi’s involvement in any wave of US banking consolidation triggered by the $66bn SunTrust-BB&T merger and justified its continued presence in China.

Under pressure to bring its cost base in line with peers, Citi executives have been upfront about the impact of technology on their 209,000-strong global workforce, including last summer’s warning that as many as half of the 20,000 operations staff in its investment bank could be supplanted by machines.

Mr Corbat’s latest comments are the most explicit the company has been on how the $8bn a year Citi spends on technology could transform its vast consumer bank, which serves 100m customers across 19 markets.

“When you think of data, AI [artificial intelligence], raw digitisation of changing processes, we still have.....
artificial_intelligence  automation  call_centres  CEOs  Citigroup  layoffs  job_destruction  job_loss 
february 2019 by jerryking
Apple’s Executive Shake-Up Readies Company for Life After iPhone
Feb. 18, 2019 | WSJ | By Tripp Mickle.

Apple Inc. is shaking up leadership and reordering priorities across its services, artificial intelligence, hardware and retail divisions as it works to reduce the company’s reliance on iPhone sales......The primary reasons for the shifts vary by division. But collectively, they reflect Apple’s efforts to transition from an iPhone-driven company into one where growth flows from services and potentially transformative technologies......Apple has also trimmed 200 staffers from its autonomous-vehicle project, and is redirecting much of the engineering resources in its services business, led by Eddy Cue, into efforts around Hollywood programming......The competitive landscape could complicate Apple’s efforts to diversify beyond the iPhone. Media services like Netflix Inc. and Spotify Technology SA have a head start and more subscribers; Google’s autonomous-vehicle initiative has logged more miles on the road; and Amazon.com Inc.’s Echo speakers have put Alexa into millions of homes.

Apple spent $14.24 billion on research and development last year, a 23% increase from the year prior........Though the iPhone still contributes about two-thirds of Apple sales, the company has encouraged investors to focus on a growing services business, which includes streaming-music subscriptions, app-store sales and mobile payments.....The services business also is key to preserving iPhone loyalty. Just as Amazon has used media and music offerings to increase the value of Prime membership, Apple executives view its mobile payments, music service and coming video offering as ways to encourage current iPhone owners to buy future Apple handsets.....Apple is also expected to lean on its artificial-intelligence team to personalize the services on people’s devices.
actors  Apple  App_Store  Apple_IDs  artificial_intelligence  autonomous_vehicles  celebrities  competitive_landscape  hardware  Hollywood  iPhone  leadership  mobile_payments  overreliance  priorities  R&D  retailers  services  smart_speakers  streaming  subscriptions  Tim_Cook 
february 2019 by jerryking
Everything still to play for with AI in its infancy
February 14, 2019 | Financial Times | by Richard Waters.

the future of AI in business up for grabs--this is a clearly a time for big bets.

Ginni Rometty,IBM CEO, describes Big Blue’s customers applications of powerful new tools, such as AI: “Random acts of digital”. They are taking a hit-and-miss approach to projects to extract business value out of their data. Customers tend to start with an isolated data set or use case — like streamlining interactions with a particular group of customers. They are not tied into a company’s deeper systems, data or workflow, limiting their impact. Andrew Moore, the new head of AI for Google’s cloud business, has a different way of describing it: “Artisanal AI”. It takes a lot of work to build AI systems that work well in particular situations. Expertise and experience to prepare a data set and “tune” the systems is vital, making the availability of specialised human brain power a key limiting factor.

The state of the art in how businesses are using artificial intelligence is just that: an art. The tools and techniques needed to build robust “production” systems for the new AI economy are still in development. To have a real effect at scale, a deeper level of standardisation and automation is needed. AI technology is at a rudimentary stage. Coming from completely different ends of the enterprise technology spectrum, the trajectories of Google and IBM highlight what is at stake — and the extent to which this field is still wide open.

Google comes from a world of “if you build it, they will come”. The rise of software as a service have brought a similar approach to business technology. However, beyond this “consumerisation” of IT, which has put easy-to-use tools into more workers’ hands, overhauling a company’s internal systems and processes takes a lot of heavy lifting. True enterprise software companies start from a different position. They try to develop a deep understanding of their customers’ problems and needs, then adapt their technology to make it useful.

IBM, by contrast, already knows a lot about its customers’ businesses, and has a huge services operation to handle complex IT implementations. It has also been working on this for a while. Its most notable attempt to push AI into the business mainstream is IBM Watson. Watson, however, turned out to be a great demonstration of a set of AI capabilities, rather than a coherent strategy for making AI usable.

IBM has been working hard recently to make up for lost time. Its latest adaptation of the technology, announced this week, is Watson Anywhere — a way to run its AI on the computing clouds of different companies such as Amazon, Microsoft and Google, meaning customers can apply it to their data wherever they are stored. 
IBM’s campaign to make itself more relevant to its customers in the cloud-first world that is emerging. Rather than compete head-on with the new super-clouds, IBM is hoping to become the digital Switzerland. 

This is a message that should resonate deeply. Big users of IT have always been wary of being locked into buying from dominant suppliers. Also, for many companies, Amazon and Google have come to look like potential competitors as they push out from the worlds of online shopping and advertising.....IBM faces searching questions about its ability to execute — as the hit-and-miss implementation of Watson demonstrates. Operating seamlessly in the new world of multi-clouds presents a deep engineering challenge.
artificial_intelligence  artisan_hobbies_&_crafts  automation  big_bets  cloud_computing  contra-Amazon  cultural_change  data  digital_strategies  early-stage  economies_of_scale  Google  hit-and-miss  IBM  IBM_Watson  internal_systems  randomness  SaaS  standardization  Richard_Waters 
february 2019 by jerryking
The robot-proof skills that give women an edge in the age of AI
February 11, 2019 | Financial Times |by Sarah O’Connor.

in a world of algorithms and artificial intelligence, communication skills and emotional intelligence — traditionally seen as female strengths — could prove key.

The latest panic about artificial intelligence is that it will deal a blow to women in the workplace..... The concerns are legitimate enough, but they fail to appreciate the big ways in which the world of work is going to change. In fact, it is quite possible the age of AI will belong to women. Men are the ones in danger of being left behind....Some AI tools may be biased against women — a risk for any group that has been historically under-represented in the workplace. Because machine learning tends to learn from historical data, it can perpetuate patterns from the past into the future......It is right to pay attention to these problems and work on solutions. Algorithms shouldn’t be given power without transparency, accountability, and human checks and balances. Top AI jobs should be held by a more diverse set of smart people.....As machines become better at many cognitive tasks, it is likely that the skills they are relatively bad at will become more valuable. This list includes creative problem-solving, empathy, negotiation and persuasion. As Andy Haldane, chief economist at the Bank of England, has put it, “the high-skill, high-pay jobs of the future may involve skills better measured by EQs (a measure of emotional intelligence) than IQs”..... increasing demand in these jobs for supplementary skills such as emotional intelligence, which has given women an edge.....as the AI era dawns, it is the right moment to overhaul the way we value these skills, and the way we teach them. With an eye on the demands of the future, we are trying to persuade girls that coding is not just for boys. So why aren’t we also trying to persuade boys that empathy is not just for girls?

We could start by changing the language we use. For too long we have talked about “soft skills”, with connotations of femininity and a lack of rigour. Let’s call them what they are: “robot-proof skills” that neither men nor women can afford to face the 21st century
21st._century  algorithms  artificial_intelligence  biases  checks_and_balances  dark_side  emotional_intelligence  EQ  future-proofing  gender_gap  machine_learning  soft_skills  smart_people  under-representation  women  workplaces  pay_attention 
february 2019 by jerryking
This Thriving City—and Many Others—Could Soon Be Disrupted by Robots - WSJ
Feb. 9, 2019 | WSJ | By Christopher Mims.

In and around the city of Lakeland, Florida you’ll find operations from Amazon, DHL (for Ikea), Walmart , Rooms to Go, Medline and Publix, a huge Geico call center, the world’s largest wine-and-spirits distribution warehouse and local factories that produce natural and artificial flavors and, of all things, glitter.

Yet a recent report by the Brookings Institution, based on data from the U.S. Census Bureau and McKinsey & Co., argues that the economic good times for Lakeland could rapidly come to an end. Brookings placed it third on its list of metros that are most at risk of losing jobs because of the very same automation and artificial intelligence that make its factories, warehouses and offices so productive......As technology drives people out of the middle class, economists say, it’s pushing them in one of two directions. Those with the right skills or education graduate into a new technological elite. Everyone else falls into the ranks of the “precariat”—the precariously employed, a workforce in low-wage jobs with few benefits or protections, where roles change frequently as technology transforms the nature of work......One step in Southern Glazer’s warehouse still requires a significant number of low-skill workers: the final “pick” station where individual bottles are moved from bins to shipping containers. This machine-assisted, human-accomplished step is common to high-tech warehouses of every kind, whether they’re operated by Amazon or Alibaba. Which means that for millions of warehouse workers across the globe, the one thing standing between them and technological unemployment is their manual dexterity, not their minds.... “I think there will be a time when we have a ‘lights out’ warehouse, and cases will come in off trucks and nobody sees them again until they’re ready to be shipped to the customer,” says Mr. Flanary. “The technology is there. It’s just not quite cost-effective yet.”
artificial_intelligence  automation  Christopher_Mims  disruption  distribution_centres  Florida  manual_dexterity  precarious  productivity  robotics  warehouses  cities  clusters  geographic_concentration  hyper-concentrations 
february 2019 by jerryking
Opinion | Abolish Billionaires - The New York Times
By Farhad Manjoo
Opinion Columnist

Feb. 6, 2019

A radical idea is gaining adherents on the left. It’s the perfect way to blunt tech-driven inequality.
Alexandria_Ocasio-Cortez  Anand_Giridharadas  artificial_intelligence  capital_acumulation  digital_economy  Farhad_Manjoo  income_distribution  income_inequality  moguls  network_effects  rhetoric  software  superstars  winner-take-all 
february 2019 by jerryking
Roger McNamee on how to tame Big Tech
February 7, 2019 | Financial Times | Roger McNamee.

Government intervention of this kind is a first step on the path to resolving the privacy issues that result from the architecture, business models and culture of internet platforms. But privacy is not the only problem we must confront. Internet platforms are transforming our economy and culture in unprecedented ways. We do not even have a vocabulary to describe this transformation, which complicates the challenge facing policymakers....Google, Facebook and other internet platforms use data to influence or manipulate users in ways that create economic value for the platform, but not necessarily for the users themselves. In the context of these platforms, users are not the customer. They are not even the product. They are more like fuel.....Google, Facebook and the rest now have economic power on the scale of early 20th-century monopolists such as Standard Oil. What is unprecedented is the political power that internet platforms have amassed — power that they exercise with no accountability or oversight, and seemingly without being aware of their responsibility to society......When capitalism functions properly, government sets and enforces the rules under which businesses and citizens must operate. Today, however, corpor­ations have usurped this role. Code and algorithms have replaced the legal system as the limiter on behaviour. Corporations such as Google and Facebook behave as if they are not accountable to anyone. Google’s seeming disdain for regulation by the EU and Facebook’s violations of the spirit of its agreement with the US FTC over user consent are cases in point......AI promises to be revolutionary. That said, it will not necessarily be a force for good. The problem is the people who create AI. They are human...McNamee recommends two areas of emphasis: regulation and innovation. As for the former, the most important requirement is to create and enforce standards that require new technology to serve the needs of those who use it and society as a whole. ...... The IoT requires our approval. Do not give it until vendors behave responsibly. Demand that policymakers take action to protect public health, democracy, privacy, innovation and the economy.
accountability  Alexa  antitrust  artificial_intelligence  biases  Big_Tech  consent  dark_side  Facebook  Google  Industrial_Internet  monopolies  personal_data  platforms  political_power  privacy  Roger_McNamee  sensors  surveillance  unintended_consequences 
february 2019 by jerryking
Opinion | Warning! Everything Is Going Deep: ‘The Age of Surveillance Capitalism’
Jan. 29, 2019 | The New York Times | By Thomas L. Friedman, Opinion Columnist.

Recent advances in the speed and scope of digitization, connectivity, big data and artificial intelligence are now taking us “deep” into places and into powers that we’ve never experienced before — and that governments have never had to regulate before. I’m talking about deep learning, deep insights, deep surveillance, deep facial recognition, deep voice recognition, deep automation and deep artificial minds.

Some of these technologies offer unprecedented promise and some unprecedented peril — but they’re all now part of our lives. Everything is going deep........how did we get so deep down where the sharks live?

The short answer: Technology moves up in steps, and each step, each new platform, is usually biased toward a new set of capabilities. Around the year 2000 we took a huge step up that was biased toward connectivity, because of the explosion of fiber-optic cable, wireless and satellites.

Suddenly connectivity became so fast, cheap, easy for you and ubiquitous that it felt like you could touch someone whom you could never touch before and that you could be touched by someone who could never touch you before.

Around 2007, we took another big step up. The iPhone, sensors, digitization, big data, the internet of things, artificial intelligence and cloud computing melded together and created a new platform that was biased toward abstracting complexity at a speed, scope and scale we’d never experienced before.....as big data got really big, as broadband got really fast, as algorithms got really smart, as 5G got actually deployed, artificial intelligence got really intelligent. So now, with no touch — but just a voice command or machines acting autonomously — we can go so much deeper in so many areas....DeepMind, the artificial intelligence arm of Google’s parent, developed an A.I. program, AlphaGo, that has now defeated the world’s top human players of the ancient strategy game Go — which is much more complex than chess — by learning from human play......Today “virtual agents” — using conversational interfaces powered by artificial intelligence — can increasingly understand your intent... just by hearing your voice.....The percentage of calls a chatbot, or virtual agent, is able to handle without turning the caller over to a person is called its “containment rate,” and these rates are steadily soaring. ....But bad guys, who are always early adopters, also see the same potential to go deep in wholly new ways.....On Jan. 20, The London Observer looked at Harvard Business School professor Shoshana Zuboff’s new book, the title of which perfectly describes the deep dark waters we’ve entered: “The Age of Surveillance Capital.”....“Surveillance capitalism,” Zuboff wrote, “unilaterally claims human experience as free raw material for translation into behavioral data. Although some of these data are applied to service improvement, the rest are declared as a proprietary behavioral surplus, fed into advanced manufacturing processes known as ‘machine intelligence,’ and fabricated into prediction products that anticipate what you will do now, soon and later. Finally, these prediction products are traded in a new kind of marketplace that I call behavioral futures markets. Surveillance capitalists have grown immensely wealthy from these trading operations, for many companies are willing to lay bets on our future behavior.”
5G  algorithms  AlphaGo  artificial_intelligence  automation  books  complexity  connectivity  dark_side  DeepMind  digitalization  gaming_the_system  human_experience  massive_data_sets  patterns  rogue_actors  Tom_Friedman  trustworthiness  virtual_agents 
january 2019 by jerryking
‘Businesses Will Not Be Able to Hide’: Spy Satellites May Give Edge From Above
Jan. 24, 2019 | The New York Times | By Cade Metz.

In October, the Chinese province of Guangdong — the manufacturing center on the southern coast that drives 12 percent of the country’s economy — stopped publishing a monthly report on the health of its local factories.

For five consecutive months, this key economic index had shown a drop in factory production as the United States applied billions of dollars in tariffs on Chinese exports. Then, amid an increasingly bitter trade war between the United States and China, the government authorities in Beijing shut the index down.

A small start-up in San Francisco began rebuilding the index, lifting information from photos and infrared images of Guangdong’s factories captured by satellites orbiting overhead. The company, SpaceKnow, is now selling this information to hedge funds, banks and other market traders looking for an edge.

High-altitude surveillance was once the domain of global superpowers. Now, a growing number of start-ups are turning it into a business, aiming to sell insights gleaned from cameras and other sensors installed on small and inexpensive “cube satellites.”..... satellite analysis will ultimately lead to more efficient markets and a better understanding of the global economy.....as well...as a check on the world’s companies and governments....use satellite imagery to track everything from illegal mining and logging operations to large-scale home demolitions. .....All of this is being driven by a drop in the cost of building, launching and operating satellites. Today, a $3 million satellite that weighs less than 10 pounds can capture significantly sharper images than a $300 million, 900-pound satellite built in the late 1990s. That allows companies to put up dozens of devices, each of which can focus on a particular area of the globe or on a particular kind of data collection. As a result, more companies are sending more satellites into orbit, and these satellites are generating more data.

And recent advances in artificial intelligence allow machines to analyze this data with greater speed and accuracy. “The future is automation, with humans only looking at the very interesting stuff,” ......The start-ups buy their data from a growing number of satellite operators, and they build the automated systems that analyze the data, pinpointing objects like cars, buildings, mines and oil tankers in high-resolution photos and other images........What began with satellite cameras is rapidly expanding to infrared sensors that detect heat; “hyperspectral” sensors that identify minerals, vegetation and other materials; and radar scanners that can build three-dimensional images of the landscape below.....
artificial_intelligence  automation  competitive_advantage  indices  imagery  informational_advantages  infrared  insights  reconnaissance  satellites  sensors  slight_edge  surveillance  trade_wars 
january 2019 by jerryking
Amazon offers cautionary tale of AI-assisted hiring
January 23, 2019 | Financial Times | by Andrew Hill.

the task of working out how to get the right people on the bus has got harder since 2001 when Jim Collins first framed it, as it has become clearer — and more research has underlined — that diverse teams are better at innovation. For good reasons of equity and fairness, the quest for greater balance in business has focused on gender, race and background. But these are merely proxies for a more useful measure of difference that is much harder to assess, let alone hire for: cognitive diversity. Might this knotty problem be solved with the help of AI and machine learning? Ming is sceptical. As she points out, most problems with technology are not technology problems, but human problems. Since humans inevitably inherit cultural biases, it is impossible to build an “unbiased AI” for hiring. “You simply have to recognise that the biases exist and put in the effort to do more than those default systems point you towards,” she says...........What Amazon’s experience suggests is that instead of sending bots to crawl over candidates’ past achievements, companies should be exploring ways in which computers can help them to assess and develop the long term potential of the people they invite to board the bus. Recruiters should ask, in Ming’s words, “Who will [these prospective candidates] be three years from now when they’re at their peak productivity inside the company? And that might be a very different story than who will deliver peak productivity the moment they walk in the door.”
heterogeneity  Amazon  artificial_intelligence  hiring  Jim_Collins  machine_learning  recruiting  teams  Vivienne_Ming  cautionary_tales  biases  diversity  intellectual_diversity  algorithms  questions  the_right_people 
january 2019 by jerryking
Company led by Google veterans uses AI to ‘nudge’ workers toward happiness - The Globe and Mail
The startup, Humu, is based in Google’s hometown and it builds on some of the people-analytics programs pioneered by the internet giant, which has studied things including the traits that define great managers and how to foster better teamwork.

Humu wants to bring similar data-driven insights to other companies. It digs through employee surveys using artificial intelligence to identify one or two behavioural changes that are likely to make the biggest impact on elevating a work force’s happiness. Then it uses e-mails and text messages to “nudge” individual employees into small actions that advance the larger goal.

At a company where workers feel that the way decisions are made is opaque, Humu might nudge a manager before a meeting to ask the members of her team for input and to be prepared to change her mind. Humu might ask a different employee to come up with questions involving her team that she would like to have answered.

At the heart of Humu’s efforts is the company’s “nudge engine” (yes, it’s trademarked). It is based on economist Richard Thaler’s Nobel Prize-winning research into how people often make decisions because of what is easier rather than what is in their best interest, and how a well-timed nudge can prompt them to make better choices.

Google has used this approach to coax employees into the corporate equivalent of eating their vegetables, prodding them to save more for retirement, waste less food at the cafeteria and opt for healthier snacks.

Using machine learning, Humu will tailor the timing, content and techniques of the messages it delivers based on how employees respond.

“Often we want to be better people,” said Laszlo Bock, Humu’s chief executive and Google’s former leader of what the company calls people operations, or human resources
Asha_Isaacs  artificial_intelligence  Google  happiness  machine_learning  Richard_Thaler  nudge  behavioural_economics  Laszlo_Bock 
january 2019 by jerryking
CSIS director warns of state-sponsored espionage threat to 5G networks - The Globe and Mail
ROBERT FIFE OTTAWA BUREAU CHIEF
STEVEN CHASE
COLIN FREEZE
OTTAWA AND TORONTO
PUBLISHED DECEMBER 4, 2018

Canada’s top spy used his first public speech to warn of increasing state-sponsored espionage through technology such as next-generation 5G mobile networks.

Canadian Security Intelligence Service director David Vigneault’s comments come as three of the country’s Five Eyes intelligence-sharing allies have barred wireless carriers from installing equipment made by China’s Huawei Technologies Co. Ltd. in the 5G infrastructure they are building to provide an even-more-connected network for smartphone users.

The United States, Australia and New Zealand have taken steps to block the use of Huawei equipment in 5G networks. Neither Canada nor Britain has done so.

On Monday, the head of Britain’s Secret Intelligence Service, known as MI6, publicly raised security concerns about Huawei telecommunications being involved in his country’s communications infrastructure.......hostile states are targeting large companies and universities to obtain new technologies.....“Many of these advanced technologies are dual-use in nature in that they could advance a country’s economic, security and military interests,”......there are five potential growth areas in Canada that are being specifically threatened, including 5G mobile technology where Huawei has been making inroads...“CSIS has seen a trend of state-sponsored espionage in fields that are crucial to Canada’s ability to build and sustain a prosperous, knowledge-based economy,”...“I’m talking about areas such as AI [artificial intelligence], quantum technology, 5G, biopharma and clean tech. In other words, the foundation of Canada’s future growth.”.....Canadian universities are largely unaware how they are vulnerable to economic espionage and the threat of infiltration by unnamed state actors who would use their expertise to gain an edge in military technologies. Huawei has developed research and development partnerships with many of Canada’s leading academic institutions.....MI6′s Alex Younger said Britain has to make a decision about Huawei after the United States, Australia and New Zealand acted against Huawei..... 5G technology – which offers faster download speeds – poses a greater national security threat than conventional mobile technology......A ban would come as a blow to Canada’s biggest telecom companies, including BCE Inc. and Telus, which have given Huawei an important role in their planned 5G networks.....Scott Jones, the new head of the Canadian Centre for Cyber Security, which is part of the Communications Security Establishment, rejected the idea of blocking Huawei, telling MPs that the country’s safeguards are adequate to mitigate against any risk.
5G  artificial_intelligence  China  CSIS  CSE  cyber_security  dual-use  espionage  Five_Eyes  Huawei  MI6  mobile  quantum_computing  spymasters  wireless  Colleges_&_Universities  infiltration 
december 2018 by jerryking
Every Company Is Now a Tech Company
Dec. 4, 2018 | WSJ | By Christopher Mims.

There was a time when the primary role of leaders at most companies was management. The technology required to do the work of a company could be bought or siloed in an “IT department,” treated more as a cost center than a source of competitive advantage.

But now we’ve entered a period of upheaval, driven by connectivity, artificial intelligence and automation. The changes affect the world of business so profoundly that every company is now a tech company. But now companies born before the first internet bubble also must realize they can no longer function as non-tech businesses......The question is, how does a non-tech company become a tech company quickly? Increasingly, the answer is bringing tech talent into the highest executive ranks, adding deeply knowledgeable and indispensable “technical co-founders” long after the company was founded......To put it another way: When faced with a competitor like Amazon, do you do as Walmart did, and invest heavily in tech firms and technical knowledge? Or do you go the way of Sears…into bankruptcy court?

In August 2016, Walmart announced it would acquire e-commerce startup Jet.com for $3.3 billion, the largest ever deal of an old-line bricks-and-mortar company buying an e-commerce company. The acquisition was about a transfusion of new minds as much as Jet’s technology, which was far ahead of Walmart’s online operation at the time....Mr. Lore is now chief of e-commerce at Walmart......Walmart’s e-commerce business revenue grew 43% in the last quarter alone....Wal-Mart is successfully pursuing a “second-mover strategy” against Amazon....Things don’t always go this smoothly. In fact, when well-established companies acquire tech-savvy startups in order to bring aboard engineers and executives--acqui-hires-- it’s usually a disaster.....Within the first three years after an acquisition, 60% of employees at a startup leave......That rate of turnover is twice that of employees hired the old-fashioned way. What’s worse, the employees who leave tend to be the most aggressive and entrepreneurial—and more likely to launch a competing startup.....For large companies stuck between the rock of disruption and the hard place of acquiring startups that can’t hold on to key employees, what’s to be done?[sounds like a cultural clash] John Chambers, who was chief executive at Cisco for more than 20 years, where he oversaw 180 acquisitions, has some answers. In his new book, “Connecting the Dots,” Mr. Chambers outlines some rules. For one, corporate cultures should align. Also, it helps if the company you’re buying already has significant traction in the market..... it’s essential to promote the leaders of acquired companies into your own ranks. Mr. Chamber’s rule at Cisco was that a third of the company’s leaders should be promoted from within, a third should be recruited from outside, and a third should come from acquisitions. .......As the competitive landscape continues to change and technology becomes ever more essential to how business is done, investments that might have seemed too risky a few years ago now may sometimes turn out to be the best path to survival.
acquihires  artificial_intelligence  automation  Amazon  books  Christopher_Mims  connecting_the_dots  CTOs  Cisco  cultural_clash  digital_savvy  e-commerce  Jet  John_Chambers  large_companies  post-deal_integration  reinvention  silo_mentality  technology  Wal-Mart 
december 2018 by jerryking
Canada’s IP strategy is not in step with our innovation and commercialization goals - The Globe and Mail
JIM HINTON AND PETER COWAN
CONTRIBUTED TO THE GLOBE AND MAIL
PUBLISHED 57 MINUTES AGO
UPDATED NOVEMBER 25, 2018
Jim Hinton is a principal at Own Innovation and Peter Cowan is a principal at Northworks IP

There is a global arms race for artificial intelligence-related intellectual property. The United States and China are amassing thousands of patent filings related to AI and machine learning.....The hype surrounding R&D funding has not translated to commercialization of AI outside of a small handful of domestic high-growth companies, such as Hatch and Sightline Innovation. This confirms what we already know: Innovation and IP funding announcements alone are not a strategy for growth. What Canada needs is a strategy to own its AI innovations and turn them into prosperity engines for the Canadian economy.

Lost in the hype around Canada becoming an AI hub is an absolute lack of follow-through to ensure intellectual property (IP) rights are preserved for current and future Canadian commercialization needs. There is currently no strategy in any of the taxpayer-funded programs ensuring IP ownership is maintained for the benefit of the Canadian economy. ......Companies such as Alphabet, Huawei and others will continue to partner with Canadian universities and use Canadian taxpayer-funded technology to their global advantage: Of the 100 or so machine learning-related patents that have been developed in Canada over the past 10 years, more than half have ended up in the hands of foreign companies such as Microsoft and IBM.......

.........To reverse the status quo, Canada’s IP strategy must include at least four key tactics: (1) IP generation, ensuring that Canadian firms own valuable IP and data stocks; (2) IP retention; (3) freedom to operate strategies for our innovative high-growth companies; and (4) alignment of the national IP strategy with the national data strategy.
artificial_intelligence  Canada  innovation  intellectual_property  machine_learning  property_rights  arms_race  commercialization  Jim_Balsillie 
november 2018 by jerryking
JPMorgan Invests in Startup Tech That Analyzes Encrypted Data - CIO Journal. - WSJ
By Sara Castellanos
Nov 13, 2018
(possible assistance to Robert Lewis)

JPMorgan Chase & Co. has invested in a startup whose technology can analyze an encrypted dataset without revealing its contents, which could be “materially useful” for the company and its clients, said Samik Chandarana, head of data analytics for the Corporate and Investment Bank division.

The banking giant recently led a $10 million Series A funding round in the data security and analytics startup, Inpher Inc., headquartered in New York and Switzerland. JPMorgan could use the ‘secret computing’ technology to analyze a customer’s proprietary data on their behalf, using artificial intelligence algorithms without sacrificing privacy.......One of the technological methods Inpher uses, called fully homomorphic encryption, allows for computations to be conducted on encrypted data, said Jordan Brandt, co-founder and CEO of the company. It’s the ability to perform analytics and machine learning on cipher text, which is plain, readable text that has been encrypted using a specific algorithm, or a cipher, so that it becomes unintelligible.

Analyzing encrypted information without revealing any secret information is known as zero-knowledge computing and it means that organizations could share confidential information to gather more useful insights on larger datasets.
algorithms  artificial_intelligence  encryption  JPMorgan_Chase  start_ups 
november 2018 by jerryking
Using Digital Tools to Move a Candy Company Into the Future - The New York Times
As told to Patricia R. Olsen
Sept. 21, 2018

explore the ways in which we can take advantage of new technologies and tools, such as artificial intelligence; how we should experiment; and whether we are even looking at the right problems. Mars is based in McLean, Va.,...... Part of my work involves prototyping, such as growing peanut plants in a fish tank using digital automation — without human intervention. To do this, I worked with a few colleagues in Mount Olive, N.J., a unit that I’m part of, though I don’t work there all the time. We implemented an automated watering and fertilizing schedule to see how the plants would grow.

We don’t only produce candy. We also offer pet care expertise and produce pet food and human food, like Uncle Ben’s Rice. With the peanut plants, we wanted to see if we could learn anything for partnering with our farmers, everything from how we might use technology to how a team comes together and tries different ideas.
career_paths  digital_strategies  Mars  women  CPG  confectionery_industry  artificial_intelligence  experimentation  howto  pets  problem_framing  problem_definition  prototyping  future  automation  human_intervention  worthwhile_problems 
september 2018 by jerryking
21 Lessons for the 21st Century,
The world in 2050. In an excerpt from his new book, “21 Lessons for the 21st Century,” Yuval Noah Harai examines nothing less than the impact of artificial intelligence on our political and econom...
books  nonfiction  artificial_intelligence 
august 2018 by jerryking
The Chip That Changed the World
Aug. 26, 2018 | WSJ | By Andy Kessler.

Integrated circuits are the greatest invention since fire—or maybe indoor plumbing. The world would be unrecognizable without them. They have bent the curve of history, influencing the economy, government and general human flourishing. The productivity unleashed from silicon computing power disrupted or destroyed everything in its path: retail, music, finance, advertising, travel, manufacturing, health care, energy. It’s hard to find anything Kilby’s invention hasn’t changed.

Now what? Despite the routine media funeral for Moore’s Law, it’s not dead yet. But it is old.......Brace yourself. When Moore’s Law finally gives up the ghost, productivity and economic growth will roll over too—unless. The world needs another Great Bend, another Kilbyesque warp in the cosmos, to drive the economy.

One hope is quantum computing, which isn’t limited by binary 1s and 0s, but instead uses qubits (quantum bits) based on Schrödinger’s quantum mechanics. .......Maybe architecture will keep the growth alive. Twenty years ago, Google created giant parallel computer systems to solve the search problem. The same may be seen for artificial intelligence, which is in its infancy. ......Energy is being disrupted but not fast enough. Where is that battery breakthrough? .........Biocomputing is another fascinating area. We already have gene editing in the form of Crispr. New food supplies and drugs may change how humans live and not die and bend the curve. But.... anything involving biology is painfully slow. ....Computing takes nanoseconds; biology takes days, weeks, even years. Breakthroughs may still come, but experiments take so long that progress lags behind. Still, I’d watch this space closely.
Andy_Kessler  artificial_intelligence  breakthroughs  Crispr  game_changers  gene_editing  Gordon_Moore  hard_to_find  history  inventions  miniaturization  Moore's_Law  Nobel_Prizes  quantum_computing  semiconductors 
august 2018 by jerryking
Passive investing is storing up trouble
August 2, 2018 | Financial Times | by Megan Greene.

I was recently informed by the owner of an artificial intelligence fund that markets do not listen to economists any more. .....A fundamental shift in market structure towards rules-based, passive investing over the past decade means a lot of trading is no longer based on fundamentals. But just because some markets do not pay attention to economists, it does not mean economists should not pay attention to these markets........AI quant funds are not waiting on tenterhooks for analysis of every non-farm payrolls report, Fed press conference, Donald Trump tweet, or earnings report. Instead, they look for trading strategies that are succeeding and adopt those strategies until a better one comes along, regardless of the underlying fundamentals. But what happens when the strategy suddenly becomes to sell everything? Will the computers find the buyers they need?.......ETFs, often set up to mimic an index, have to buy more of equities rising in price, sending those stock prices even higher. ETFs similarly ignore fundamentals.....This creates a piling-on effect as funds buy more of these increasingly expensive stocks and less of the cheaper ones in their indices...Risks of a bubble arise when there is no regard for underlying fundamentals or price. It is reasonable to assume a sustained market correction would lead to stocks that were disproportionately bought because of ETFs and index funds being disproportionately sold.

But again, in a crisis will the ETF managers find liquid markets? ....Passive investors and quant funds could also threaten the economy by making markets vastly more complex, noisy and opaque. They send mixed signals to active investors about what the fair value of a stock is. That could cause a significant misallocation of capital.

The danger is exacerbated by the speed at which trading is now done. The average holding period for a security on the New York Stock Exchange has fallen from two months in 2008 to just under 20 seconds today.......Systemic failures, misallocation of capital and dried up liquidity could cause a bear market, dragging on growth when the economic backdrop is already lacklustre......So even though passive investors ignore economists, economists should pay attention to risks posed by the shift in market structure they represent....This is not to say that index funds, ETFs and AI quant funds are necessarily bad. But the real test will come when there is a sudden crisis followed by a sustained bear market.
active_investing  artificial_intelligence  bear_markets  economists  ETFs  holding_periods  index_funds  investing  liquidity  misallocations  NYSE  passive_investing  piling_on  risks  systemic_failures  rules-based  bubbles  quantitative  market_fundamentals  crisis  dark_side  pay_attention 
august 2018 by jerryking
Artificial intelligence and jobs: What’s left for humanity will require uniquely human skills - The Globe and Mail
July 27, 2018 |CONTRIBUTED TO THE GLOBE AND MAIL by STEVE WOODS.

Where should we look for this final archipelago of human employment? The best place to start is deep within ourselves. As much as we pride ourselves on advanced skills such as mathematics and chess, humans are not born innately aware of algebra or checkmate. We are, instead, a social species. We are born innately aware of others, their reactions to us and our relationships with them. Removing a person from a social environment is so harmful that it is deemed to be a form of torture and is banned by the Geneva Convention.

When we attempt to use machines to replace the role of humans in our social lives, the response is immediate and negative......we, as a society and as a species, don’t want AI to replace our social interactions and our relationships. It’s a part of what makes us human and it’s a part that we intend to keep.....areas where we don’t desire AI replacement: relationships, trust, guidance, caring, nurturing and social interaction are traits that these post-AI jobs will share.
artificial_intelligence  automation  relationships  emotions  emotional_intelligence  empathy  EQ  humanity  creative_destruction  Joseph_Schumpeter  character_traits  AlphaGo  IBM_Watson 
july 2018 by jerryking
Commodity trading enters the age of digitisation
July 9, 2018 | Financial Times | by Emiko Terazono.

Commodity houses are on the hunt for data experts to help them gain an edge after seeing their margins squeezed by rivals......commodity traders are seeking ways of exploiting their information to help them profit from price swings.

“It is really a combination of knowing what to look for and using the right mathematical tools for it,” ........“We want to be able to extract data and put it into algorithms,” .......“We then plan to move on to machine learning in order to improve decision-making in trading and, as a result, our profitability.” The French trading arm is investing in people, processes and systems to centralize its data — and it is not alone.

“Everybody [in the commodity world] is waking up to the fact that the age of digitisation is upon us,” said Damian Stewart at headhunters Human Capital.

In an industry where traders with proprietary knowledge, from outages at west African oilfields to crop conditions in Russia, vied to gain an upper hand over rivals, the democratisation of information over the past two decades has been a challenge......the ABCDs — Archer Daniels Midland, Bunge, Cargill and Louis Dreyfus Company — all recording single-digit ROE in their latest results. As a consequence, an increasing number of traders are hoping to increase their competitiveness by feeding computer programs with mountains of information they have accumulated from years of trading physical raw materials to try and detect patterns that could form the basis for trading ideas.......Despite this new enthusiasm, the road to electronification may not come easily for some traders. Compared to other financial and industrial sectors, “they are coming from way behind,” said one consultant.

One issue is that some of the larger commodities traders face internal resistance in centralising information on one platform.

With each desk in a trading house in charge of its profit-and-loss account, data are closely guarded even from colleagues, said Antti Belt, head of digital commodity trading at Boston Consulting Group. “The move to ‘share all our data with each other’ is a very, very big cultural shift,” he added.

Another problem is that in some trading houses, staff operate on multiple technology platforms, with different units using separate systems.

Rather than focusing on analytics, some data scientists and engineers are having to focus on harmonising the platforms before bringing on the data from different parts of the company.
ADM  agribusiness  agriculture  algorithms  artificial_intelligence  Bunge  Cargill  commodities  data_scientists  digitalization  machine_learning  traders  food_crops  Louis_Dreyfus  grains  informational_advantages 
july 2018 by jerryking
The AI arms race: the tech fear behind Donald Trump’s trade war with China | Financial Times
Shawn Donnan in Washington YESTERDAY

While the headlines about the Trump administration’s trade war with Beijing often focus on raw materials such as steel, aluminium and soyabeans, the underlying motivation of the new protectionist mood is American anxiety about China’s rapidly growing technological prowess.......
At a time when the US is engaged in a battle for technological pre-eminence with China, the ZGC project is exactly the sort of state-backed Chinese investment that American politicians across the political spectrum view with scepticism.

“China has targeted America’s industries of the future, and President Donald Trump understands better than anyone that if China successfully captures these emerging industries, America will have no economic future,” .....US tariffs on $34bn in imports from China that are due to take effect on Friday as part of a squeeze intended to end what the US says has been years of state-endorsed Chinese intellectual property theft. But it is also part of a broader battle against what the White House has labelled China’s “economic aggression”......Viewed from America, President Xi Jinping’s Made in China 2025 industrial strategy is a state-led effort to establish Chinese leadership in the technologies of the next generation of commerce and military equipment — notably AI, robotics and gene editing.

Many US officials are now questioning one of the basic assumptions about how the American economy operates: its openness to foreign investment....While some technology executives extol the potential for co-operation in areas such as AI, the Washington establishment increasingly sees them as central to a growing geopolitical competition....Many Chinese investors are looking for US companies that they can help move into China. .....Even though Mr Trump’s focus on Chinese technology has strong bipartisan support in Washington, its tactics have been heavily criticised. The biggest blunder, many critics argue, has been the Trump administration’s willingness to wage concurrent trade wars. The IP-driven tariffs push against China has been accompanied by one that has hit allies such as Canada and the EU that might have joined a fight against Beijing.

........“We’re treating the Chinese better than we are treating our friends,” says Derek Scissors, a China expert at the conservative American Enterprise Institute, who sees the tariffs Mr Trump is threatening against European car imports as a similar bit of malpractice.
arms_race  artificial_intelligence  China  CFIUS  Donald_Trump  economic_warfare  economic_aggression  FDI  geopolitics  international_trade  investors  investing  intellectual_property  industrial_policies  protectionism  politicians  robotics  One_Belt_One_Road  security_&_intelligence  Silicon_Valley  SOEs  start_ups  theft  U.S.  venture_capital  Washington_D.C. 
july 2018 by jerryking
The Morning Download: Computing’s Future Lies at Edge of Network, Just Before the Cloud - CIO Journal. - WSJ
By Steve Rosenbush
Jun 20, 2018

For years, computing has been centralized in one place or another. First, the data center, and later massive clouds. Now, networks are taking a more decentralized structure, with power located at the so-called edge, be it a retail environment, an oil rig or an automobile. On Tuesday, Hewlett Packard Enterprise Co. said it will invest $4 billion during the next four years to accelerate innovation in what HPE calls “the intelligent edge.”

Edge of opportunity. “We see significant areas for growth … (as) more assets and ‘things’ come online and the amount of data generated continues to grow exponentially,” HPE CEO Antonio Neri told CIO Journal’s Sara Castellanos in an email. The number of devices connected to the internet will reach 20.4 billion by 2020, up from 8.4 billion in 2017, according to Gartner Research Inc. By 2021, 40% of enterprises will have an edge computing strategy in place, up from about 1% in 2017, Gartner says.

The payoff. Stewart Ebrat, CIO at bridal gown and fashion company Vera Wang Co., an HPE customer, maintains that with data analytics and Bluetooth-enabled beacon devices at the edge, a salesperson could know more about a prospective customer’s preferences as soon as they walk into a brick-and-mortar store. Says Mr. Ebrat: “The customer has always been number one (at Vera Wang), but technology is going to enhance that experience even further.”
cloud_computing  decentralization  edge  future  Industrial_Internet  IT  artificial_intelligence  centralization  machine_learning  HPE  HP  data_centers 
june 2018 by jerryking
Vertical media mergers are just so 19th century | Financial Times
June 21, 2018 | Financial Times | Anne-Marie Slaughter.

Media companies are falling over themselves to merge with one another right now. AT&T took the US to court over the right to buy TimeWarner, and Comcast and Disney are engaged in a bidding war for some of 21st Century Fox. Big looks set to get bigger. Yet according to our best thinkers on the future of capitalism, the corporate titans driving these decisions are heading firmly backward.

AT&T and Comcast are communications companies that are attempting to go vertical and control every layer of a media empire from underground cables to the creation of content....Andrew Carnegie was determined to own coal mines and railroads as well as steel mills. The goal was control from top to bottom, closed access and economies of scale.

But that is old-fashioned thinking, according to the current crop of books on the dramatic economic changes being wreaked in the next phase of the information age. They argue that vertical integration amounts to building silos in an era that will be dominated by platforms — owning in an era of renting — and looking for mass markets when customers want individualized products.

Hemant Taneja makes a strong case for “customised microproduction and finely targeted marketing” in his book Unscaled. An investor for the Boston-based firm General Catalyst, he does not question the value of having many customers rather than few. But he argues that fast-growing companies in sectors ranging from energy to healthcare and education are succeeding because they customise their goods and services to a “market of one”.

The rise of artificial intelligence and cloud computing allows these companies to “rent scale”, he writes. Small, nimble companies can now out-compete big ones in specific markets, adding scale as they need to.....Netflix’s market value exceeded that of Comcast back in May and it is now bigger than Disney. Its global headcount is 5,500, nearly one-fifth of Time Warner’s and one-50th of AT&T’s. Netflix does not have the size to build as large in-house AI capabilities. But a quick search for “media data analytics” reveals a score of companies. Why pay for that capability when you can rent it
Andrew_Carnegie  Anne-Marie_Slaughter  artificial_intelligence  books  cloud_computing  end_of_ownership  entertainment_industry  Netflix  platforms  scaling  size  vertical_integration  AT&T  Comcast  customization  Disney  gazelles  nimbleness  mass_media  personalization  mergers_&_acquisitions  21st_Century_Fox  Time_Warner  19th_century  microproducers  target_marketing  unscalability  silo_mentality 
june 2018 by jerryking
The future of computing is at the edge
June 6, 2018 | FT | by Richard Waters in San Francisco.

With so much data being produced, sending it all to cloud does not make economic sense.

The economics of big data — and the machine learning algorithms that feed on it — have been a gift to the leading cloud computing companies. By drawing data-intensive tasks into their massive, centralised facilities, companies such as Amazon, Microsoft and Google have thrived by bringing down the unit costs of computing.

But artificial intelligence is also starting to feed a very different paradigm of computing. This is one that pushes more data-crunching out to the network “edge” — the name given to the many computing devices that intersect with the real world, from internet-connected cameras and smartwatches to autonomous cars. And it is fuelling a wave of new start-ups which, backers claim, represent the next significant architectural shift in computing.....nor.ai, an early-stage AI software start-up that raised $12m this month, is typical of this new wave. Led by Ali Farhadi, an associate professor at University of Washington, the company develops machine learning algorithms that can be run on extremely low-cost gadgets. Its image recognition software, for instance, can operate on a Raspberry Pi, a tiny computer costing just $5, designed to teach the basics of computer science......That could make it more economical to analyse data on the spot rather than shipping it to the cloud. One possible use: a large number of cheap cameras around the home with the brains to recognise visitors, or tell the difference between a burglar and a cat.

The overwhelming volume of data that will soon be generated by billions of devices such as these upends the logic of data centralisation, according to Mr Farhadi. “We like to say that the cloud is a way to scale AI, but to me it’s a roadblock to AI,” he said. “There is no cloud that can digest this much data.”

“The need for this is being driven by the mass of information being collected at the edge,” added Peter Levine, a partner at Silicon Valley venture capital firm Andreessen Horowitz and investor in a number of “edge” start-ups. “The real expense is going to be shipping all that data back to the cloud to be processed when it doesn’t need to be.”

Other factors add to the attractions of processing data close to where it is collected. Latency — the lag that comes from sending information to a distant data centre and waiting for results to be returned — is debilitating for some applications, such as driverless cars that need to react instantly. And by processing data on the device, rather than sending it to the servers of a large cloud company, privacy is guaranteed.

Tobias Knaup, co-founder of Mesosphere, another US start-up, uses a recent computing truism to sum up the trend: “Data has gravity.”....Nor are the boundaries between cloud and edge distinct. Data collected locally is frequently needed to retrain machine learning algorithms to keep them relevant, a computing-intensive task best handled in the cloud. Companies such as Mesosphere — which raised $125m this month, taking the total to more than $250m — are betting that this will give rise to technologies that move information and applications to where they are best handled, from data centres out to the edge and vice versa...Microsoft unveiled image-recognition software that was capable of running on a local device rather than its own data centres.
cloud_computing  edge  future  Industrial_Internet  IT  low-cost  artificial_intelligence  centralization  machine_learning  data_centers  decentralization  Microsoft  computer_vision  Richard_Waters 
june 2018 by jerryking
Google and Repsol team up to boost oil refinery efficiency
June 3, 2018 | Financial Times | Anjli Raval in London YESTERDAY

Repsol will use Cloud ML, Google’s machine learning tool, to optimise the performance of its 120,000 barrel-a-day Tarragona oil refinery on the east coast of Spain, near Barcelona.

A refinery is made up of multiple divisions, including the unit that distils crude into various components to be processed into fuels such as gasoline and diesel and the entity that converts heavy residual oils into lighter, more valuable products.

Google’s technology will be used to analyse hundreds of variables that measure pressure, temperature, flows and processing rates among other functions for each unit at Tarragona. Repsol hopes this will boost margins by 30 cents per barrel at the facility and plans to roll out the technologies across its five other refineries.

Energy companies are increasingly looking to use the type of analytics often employed by companies such as Google and Amazon for consumer data across their operations, from boosting the performance of drilling rigs to helping to deliver greater returns from refineries.

“Until very recently, [oil and gas] companies have not had the tools or the capabilities needed to operate these assets at their maximum capacity,” McKinsey, the professional services firm, said in a recent report. “Analytics tools and techniques have advanced far and fast.”
artificial_intelligence  efficiencies  energy  Google  oil_industry  oil_refiners  Silicon_Valley  Repsol  tools  machine_learning 
june 2018 by jerryking
The challenger - Technopolitics
Mar 15th 2018 | HONG KONG AND SAN FRANCISCO.

Technology is rarely, in and of itself, ideological. But technosystems have an ideological side—witness the struggles of open-source advocates against proprietary-software developers—and can be used to ideological ends. The global spread of a technosystem conceived in, and to an unknown extent controlled by, an undemocratic, authoritarian regime could have unprecedented historical significance.

China is not just in a better position to challenge America’s hegemony than it used to be. It is a good time to do so, too. It is not only the roll out of 5G. AI has started to move from the tech world to conventional businesses; quantum computing seems about to become useful. All this creates openings for newcomers, especially if backed by a state that takes a long view and doesn’t need a quick return......To focus on individual companies, though, is to miss the point. China’s leaders want to bind firms, customers and government agencies together with “robust governance”, in the words of Samm Sacks of the Centre for Strategic and International Studies (CSIS), a think-tank in Washington, DC. They want to build a technosystem in which incentives to use other people’s technology are minimised. These are, as it happens, the same goals as those of the companies which run America’s large technology platforms, whether they are operating systems, social networks or computing clouds.

Gardening tools

A cardinal rule of managing such walled gardens is to control access. Developers of apps for Apple’s iPhone have to go through a lengthy application process with an uncertain outcome; for example, in an unexpected but welcome development, the firm now seems to reject apps using emojis. Similarly, foreign technology firms that want to sell their wares in China face at least six different security reviews, each of which can be used to delay or block market access. As with America’s worries about Huawei, this is not entirely unreasonable. The NSA has in the past exploited, or created, vulnerabilities in hardware sold by American companies. Local firms, for their part, are pushed to use “indigenous and controllable core cyber-security technology”, in the words of a report presented at last year’s National People’s Congress.

In the driving seat
Good platform managers also ensure that all parts of the system work for the greater good. In China this means doing the government’s bidding, something which seems increasingly expected of tech companies. About three dozen tech companies have instituted Communist Party committees in the past few years. There are rumours that the party is planning to take 1% stakes in some firms, including Tencent, not so much to add to the government’s control as to signal it—and to advertise that the company enjoys official blessing.

Many of China’s tech firms help develop military applications for technology, too, something called “civil-military fusion”. Most American hardware-makers do the same; its internet giants, not so much. “There’s a general concern in the tech community of somehow the military-industrial complex using their stuff to kill people incorrectly, if you will,” Eric Schmidt, the head of the Pentagon’s Defence Innovation Advisory Board said last November, when he was still Alphabet’s executive chairman. When it recently emerged that Google was helping the Pentagon with the AI for a drone project, some of its employees were outraged.

And then there is the walled gardens’ most prized bloom: data. China’s privacy regulations can look, on the face of it, as strict as Europe’s. But privacy is not a priority in practice. Control is.
China  U.S._Navy  ecosystems  Silicon_Valley  semiconductors  artificial_intelligence  quantum_computing  intellectual_property  military-industrial_complex  dual-use 
april 2018 by jerryking
BlackRock bulks up research into artificial intelligence
February 19, 2018 | FT | Robin Wigglesworth in New York and Chris Flood in London.

BlackRock is establishing a “BlackRock Lab for Artificial Intelligence” in Palo Alto, California.....The lab will “augment our current teams and accelerate our efforts to bring the benefits of these technologies to the entirety of the firm and to our clients”.....The asset management industry is particularly interested in the area, as they try to improve the performance of their fund managers, automate back-office functions to cut costs and enhance their client outreach by analysing vast amounts of internal and external data....\quantitative managers are “engaged in an arms race” as data analysis techniques that work today will not necessarily be relevant in five years.

“Big data offers a world of possibilities for generating alpha [market beating returns] but traditional techniques are not good enough to analyse the huge volumes of information involved,” .....The data centre is looking for another dozen or so hires for its launch, underlining the ravenous appetite among asset managers to snap up more quantitative analysts adept at trawling through data sets like credit card purchases, satellite imagery and social media for investment signals.
alpha  artificial_intelligence  asset_management  arms_race  automation  alternative_data  BlackRock  back-office  quantitative  Silicon_Valley 
february 2018 by jerryking
Singapore experiments with smart government
January 22, 2018 | FT | by John Thornhill.

Singapore has a reputation as a free-trading entrepôt, beloved of buccaneering Brexiters. ....But stiff new challenges confront Singapore, just as they do all other countries, in the face of the latest technological upheavals. Is the smart nation, as it likes to style itself, smart enough to engineer another reboot?.....Singapore is becoming a prime test bed for how developed nations can best manage the potentially disruptive forces unleashed by powerful new technologies, such as advanced robotics and artificial intelligence...Naturally, Singapore’s technocratic government is well aware of those challenges and is already rethinking policy and practice. True to its heritage, it is pursuing a hybrid approach, mixing free market principles and state activism.

Rather than passively reacting to the technological challenges, the island state is actively embracing them....“The real skill of Singapore has been to reverse engineer the needs of industry and to supply them in a much more cost-effective way than simply writing a cheque,” says Rob Bier, managing partner of Trellis Asia, which advises high-growth start-ups...To take one example, the country has become an enthusiastic promoter of autonomous vehicles. The government has created one of the most permissive regulatory regimes in the world to test driverless cars.....GovTech’s aim is to help offer seamless, convenient public services for all users, creating a truly digital society, economy and government. To that end, the government is acting as a public sector platform, creating a secure and accessible open-data infrastructure for its citizens and companies. For example, with users’ permission, Singapore’s national identity database can be accessed by eight commercial banks to verify customers with minimal fuss. A public health service app now allows parents to keep check of their children’s vaccinations.

By running with the technological wolves, Singapore is clearly hoping to tame the pack.
Singapore  autonomous_vehicles  dislocations  traffic_congestion  aging  smart_government  disruption  robotics  automation  artificial_intelligence  test_beds  reboot  city_states  experimentation  forward-thinking  open-data  privacy  reverse_engineering 
january 2018 by jerryking
What the Tax Bill Fails to Address: Technology’s Tsunami -
DEC. 20, 2017 | The New York Times | Farhad Manjoo.

Manjoo posits that the Republican tax bill is the wrong fix for the wrong problem, given how tech is altering society and the economy....The bill (the parachute) does little to address the tech-abetted wave of economic displacement (the tsunami) that may be looming just off the horizon. And it also seems to intensify some of the structural problems in the tech business, including its increasing domination by five giants — Apple, Amazon, Microsoft, Facebook and Alphabet, Google’s parent company — which own some of the world’s most important economic platforms.....some in Silicon Valley think the giants misplayed their hand in the legislation. In pursuing short-term tax advantages, they missed a chance to advocate policies that might have more broadly benefited many of their customers — and improved their images, too......This gets back to that looming tsunami. Though many of the economy’s structural problems predate the last decade’s rise of the tech behemoths, the innovations that Silicon Valley has been working on — things like e-commerce, cloud storage, artificial intelligence and the general digitization of everything and everyone around you — are some of the central protagonists in the economic story of our age.

Among other economic concerns, these innovations are implicated in the rise of inequality; the expanding premium on education and skills; the decimation and dislocation of retail jobs; the rising urban-rural divide, and spiking housing costs in cities; and the rise of the “gig” economy of contract workers who drive Ubers and rent out their spare bedrooms on Airbnb....technology is changing work in a few ways. First, it’s altering the type of work that people do — for instance, creating a boom in e-commerce warehouse jobs in large metro areas while reducing opportunities for retail workers in rural areas. Technology has also created more uncertainty around when people work and how much they’ll get paid.
Farhad_Manjoo  preparation  job_loss  job_displacement  Silicon_Valley  tax_codes  corporate_concentration  platforms  income_inequality  short-sightedness  e-commerce  cloud_computing  artificial_intelligence  gig_economy  precarious  automation  uncertainty  universal_basic_income  digitalization  Apple  Amazon  Netflix  Microsoft  Facebook  Alphabet  Google  inconsistent_incomes  Big_Tech  FAANG 
december 2017 by jerryking
Ten Years Out
December 5 2017 | FT | By Gideon Rachman, James Kynge, Vanessa Houlder and Richard Waters.

From massive migration to prying governments, businesses will have to weather startling changes over the next decade.....It can be difficult, when assailed daily by news of populism, terrorism and cyber hacking, to look to anything beyond the next crisis. Yet business leaders need to focus on the future. What, for example, does it mean for employers that by 2027, Africa’s population will have grown by a third and Europe’s will have flatlined? How will companies cope when governments expect them to gather more staff data and play ever larger roles in enforcing tax laws?

In Ten Years Out, four senior FT journalists outline what they see as the biggest challenges that no chief executive will be able to ignore. They also provide some tips on how companies can best prepare themselves for the changes that are coming.
forecasting  trends  CEOs  challenges  migration  tax  artificial_intelligence  China  Richard_Waters 
december 2017 by jerryking
Novartis’s new chief sets sights on ‘productivity revolution’
SEPTEMBER 25, 2017 | Financial Times | Sarah Neville and Ralph Atkins.

The incoming chief executive of Novartis, Vas Narasimhan, has vowed to slash drug development costs, eyeing savings of up to 25 per cent on multibillion-dollar clinical trials as part of a “productivity revolution” at the Swiss drugmaker.

The time and cost of taking a medicine from discovery to market has long been seen as the biggest drag on the pharmaceutical industry’s performance, with the process typically taking up to 14 years and costing at least $2.5bn.

In his first interview as CEO-designate, Dr Narasimhan says analysts have estimated between 10 and 25 per cent could be cut from the cost of trials if digital technology were used to carry them out more efficiently. The company has 200 drug development projects under way and is running 500 trials, so “that will have a big effect if we can do it at scale”.......Dr Narasimhan plans to partner with, or acquire, artificial intelligence and data analytics companies, to supplement Novartis’s strong but “scattered” data science capability.....“I really think of our future as a medicines and data science company, centred on innovation and access.”

He must now decide where Novartis has the capability “to really create unique value . . . and where is the adjacency too far?”.....Does he need the cash pile that would be generated by selling off these parts of the business to realise his big data vision? He says: “Right now, on data science, I feel like it’s much more about building a culture and a talent base . . . ...Novartis has “a huge database of prior clinical trials and we know exactly where we have been successful in terms of centres around the world recruiting certain types of patients, and we’re able to now use advanced analytics to help us better predict where to go . . . to find specific types of patients.

“We’re finding that we’re able to significantly reduce the amount of time that it takes to execute a clinical trial and that’s huge . . . You could take huge cost out.”...Dr Narasimhan cites one inspiration as a visit to Disney World with his young children where he saw how efficiently people were moved around the park, constantly monitored by “an army of [Massachusetts Institute of Technology-]trained data scientists”.
He has now harnessed similar technology to overhaul the way Novartis conducts its global drug trials. His clinical operations teams no longer rely on Excel spreadsheets and PowerPoint slides, but instead “bring up a screen that has a predictive algorithm that in real time is recalculating what is the likelihood our trials enrol, what is the quality of our clinical trials”.

“For our industry I think this is pretty far ahead,” he adds.

More broadly, he is realistic about the likely attrition rate. “We will fail at many of these experiments, but if we hit on a couple of big ones that are transformative, I think you can see a step change in productivity.”
algorithms  analytics  artificial_intelligence  attrition_rates  CEOs  data_driven  data_scientists  drug_development  failure  Indian-Americans  multiple_targets  Novartis  pharmaceutical_industry  predictive_analytics  productivity  productivity_payoffs  product_development  real-time  scaling  spreadsheets  Vas_Narasimhan 
november 2017 by jerryking
Donald Trump’s unwitting surrender to China
November 22, 2017 | FT | Edward Luce.

If you want to read a nation’s priorities, look at its budget. Mr Trump’s main ambition is to cut the US corporate tax rate to 20 per cent. During Eisenhower’s time, the marginal income tax rate was above 90 per cent. That did not stop US public and private ingenuity from racing ahead of the Soviets. Today America is the world’s technological leader. With Mr Trump in the cockpit, tomorrow may look very different.
Edward_Luce  China  China_rising  America_in_Decline?  ingenuity  artificial_intelligence  Sputnik  space_warfare  unintended_consequences 
november 2017 by jerryking
Amazon Echo Review: Second Generation, Still in First Place
Oct. 25, 2017 | WSJ | By Joanna Stern

Head of the Class

The real reason to buy an Echo has nothing to do with good looks or mics. It’s all about invisible Alexa. Generally speaking, all of Alexa’s smarts work on all the devices. And in the AI-assistant race against Google and Apple, Amazon has kept its early lead in some key areas:

* A deep ecosystem. With over 25,000 voice apps, or “skills,” and multiple hardware partners integrating Alexa, Amazon’s AI platform has become the most advanced voice operating system. Google has made some headway with third-party apps, but Alexa still has the edge with more news, ride-hailing, to-do list and kitchen-friendly apps. Google’s Assistant, however, does excel at answering random questions better. Come on, Alexa, you should know wool doesn’t go in the dryer.
* A smarter smart home. Amazon still has Google beat in smart-home control. Case in point: Alexa devices work with more connected thermostat brands than Google Home does. If you are especially interested in smart home, check out the $150 Echo Plus. It has all of the new Echo’s refinements, plus built-in wireless technology for home control without the need for third-party hubs.
* A stream of new features. Earlier this month, Echos got the ability to recognize multiple voices; your voice becomes a password. When I want to reorder breath mints, Alexa knows me and doesn’t ask for a PIN. Back in May, Amazon turned Alexa into a telephone operator: You can call others with the Alexa app or with an Echo. In June, Alexa got the ability to name different kitchen timers (one for the Brussels sprouts, one for the chicken). Reminder: Google Home has a number of these features as well. And Siri still can’t set multiple timers.

Despite Amazon’s lead, the Alexa apps for iOS and Android are in dire need of a redesign. Finding controls you want is harder than finding your bag at baggage claim. The Settings menu itself feels like an entirely different app. I made a video to show how voice recognition works, partly because it confused me so much at first.
Amazon_Echo  Alexa  Apple_HomePod  Google_Home  virtual_assistants  personal_assistants  voice_assistants  smart_homes  Siri  connected_devices  artificial_intelligence  voice_interfaces 
october 2017 by jerryking
Amazon’s Alexa allies with Microsoft’s Cortana to take on Google, Siri
AUGUST 30, 2017 | The Globe and Mail | SUPANTHA MUKHERJEE AND MUNSIF VENGATTIL for REUTERS.

Amazon.com Inc and Microsoft Corp have joined forces to let their voice-controlled virtual assistants talk to each other, offering users the ability to seamlessly tap into work, their homes and shop online.

The partnership is the first time two technology companies open up their artificial intelligence-powered virtual aides to each other, and will be aimed at outsmarting rivals Google Assistant and Apple's Siri.

The move in itself is rare as most virtual assistants are known to use data from their own ecosystems and not talk to one another......Not to be left behind, Alphabet Inc said on Wednesday Google Assistant will soon be available on third-party speakers and other home appliances. (http://bit.ly/2vERgEc)

"Starting later this year, with manufacturers like LG, you'll be able to control your appliances, including washers, dryers, vacuums and more from your Assistant on your smart speaker, Android phone or iPhone," Google said.
Siri  Alexa  Cortana  artificial_intelligence  Amazon  Microsoft  Google  Google_Assistant  LG  Apple  partnerships  smart_speakers 
september 2017 by jerryking
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