Monthly Archives: June 2017

Wall Street Journal (subscription)

The Optimistic Promise of Artificial Intelligence Wall Street Journal (subscription) Artificial intelligence may be one of the technology world's current obsessions, but many people find it scary, envisioning robots taking over the world. Two top experts in the field Andrew Ng, a Stanford University adjunct professor and former AI ...

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The Optimistic Promise of Artificial Intelligence - Wall Street Journal (subscription)

Talking about artificial intelligence is in season for Europes corporate executives. Just dont mention its shortcomings.

The C-suite is eager to tout its abilities in riding the 21st-century wave of automation by using sophisticated machine learning or shop-floor robots. Mentions of the phrase artificial intelligence on earnings calls are surging, as Bloomberg Intelligences Michael McDonough hasnoted.

In a world where CEOs get more credit for cutting costs and buying back shares than opening factories or hiring staff, technology-driven efficiency is a carrot to dangle in front of shareholders. Stock-market valuations are stretched and spending opportunities are rarebut processing power is abundant and data storage cheap.

Thats why executives are conjuring up the promise of lower costs, more revenue or something in between. Deutsche Telekom and Royal Bank of Scotland are turning to chatbotsa digital replacement for call centers that could shave billions off costs in the next five years. Frances BNP Paribas and publisher Wolters Kluwer are trying to boost revenue, and are using machines to screen financial markets or customer databases and trigger automatic alerts.

Siemens computers are having a go at running gas turbines more efficiently than humans. And dont forget the blue-collar world: Logistics firms Deutsche Post and DHL are talking up the idea of using robots alongside workers on the warehouse floor.

But theres remarkably little talk of the limits of automation. What is the acceptable failure rate of these projects? Outside of games like Go or poker, just how suited are machines to the corporate world? Are some algorithms too expensive, as Netflix once found out? Theres a risk that disappointing results lead to an exaggerated corporate pullback, as the Harvard Business Review warned in April.

Machines can fail. Chatbots do so very publicly: Microsoft shut down a bot called Tay after pranksters pushed it to make racist, sexist and pornographic remarks. Earlier this year, Facebook went back to the drawing board after its bots hit a failure rate of 70 percent, according to The Information.

Failure is fine, but the acceptable failure rate of an intelligent vehicle or a computer-controlled turbine is probably different to a bum steer on an electricity bill. That can be the difference between an easy path to cost savings and a complex, long-term investment that doesnt work as intended.

Then theres the question of whether machines are always suitable. Machine learning works best in an environment with rules and huge numbers of data points. That might work with cars driving through heavy traffic governed by laws, or with achieving the best price for selling a big block of shares.

It might not work well in deciding where to invest a hedge funds money, for example, or recommending products to customers without much previous data to go on. The minute things get fuzzyeither due to a lack of rules, an unclear evaluation of success or a lack of dataartificial intelligence performs poorly, according to Pictet strategist Edgar van Tuyll.

These limitations mean its not yet clear that the cost of automation will be offset by savings in human capital. Hiring a data scientist can cost more than $200,000, according to Bloomberg News. Flight-bookings company Amadeus has 40 of them. Siemens says it has more than 200 A.I. specialists running various projects. And even Silicon Valley has its grunt workers: Facebook is hiring 3,000 content moderators, on top of 4,500 existing ones. A.I. cheerleader Amazon has 341,000 employeesthree times the number it had in 2012.

There are good reasons to talk about A.I. and boast of its successes. But opening up about failure will help, too.

This column does not necessarily reflect the opinion of Bloomberg LP and its owners.

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The Limits of Artificial Intelligence - Bloomberg

The US Department of Defense is struggling to get its arms around all of the new security issues that have come with our current technological explosion. One unexpected consideration on the table is placing stricter limitations on investment capital from China flowing into American companies that are working on artificial intelligence.

If you had any doubt that Russian hackers attempted to meddle with the United States electoral

Technology is the fastest growing industry in the American economy according to recent data. And with all the political talk about JOBS, JOBS, JOBS, its a bit surprising to see the government floating plans to limit investment in American companies. But thats exactly what the Pentagon is proposing according to Reuters. From the report:

Of particular concern is Chinas interest in fields such as artificial intelligence and machine learning, which have increasingly attracted Chinese capital in recent years. The worry is that cutting-edge technologies developed in the United States could be used by China to bolster its military capabilities and perhaps even push it ahead in strategic industries.

The U.S. government is now looking to strengthen the role of the Committee on Foreign Investment in the United States (CFIUS), the inter-agency committee that reviews foreign acquisitions of U.S. companies on national security grounds.

Reuters was able to view an unreleased Pentagon report that outlines the ways in which Chinese investors have found loopholes in CFIUS that allow them to avoid setting off any regulatory triggers. The report recommends that new legislation be drafted to update the rules governing foreign investment. It also advises that a list of critical technologies be compiled and restrictions should be placed on Chinese investment in those areas of development. Defense Secretary Jim Mattis spoke to the US Senate at a hearing on Tuesday and he insisted that the CFIUS needs to be updated to deal with todays situation.

The second most powerful man in the Senate, John Cornyn, has begun drafting legislation according to one of his aides. You heard that right. A top Republican is pushing for more regulation and less investment. Time will tell if Republicans can get behind another one of the Pentagons recommendations that goes against everything they stand for. The report is asking for greater flexibility on the immigration policy for Chinese graduate students studying in the US. It suggests that these students should be allowed to stay in the US after finishing their studies.

The research firm Rhodium Group found that China funneled $45.6 billion into completed acquisitions and greenfield investments in the US last year. It has increased that investment by 100 percent in 2017. Tech lobbyists will surely be out in full force to fight any sort of regulatory increases.

The new age of security threats includes encryption, online organization, cyberattacks, rapid spread of disinformation, autonomous vehicles, drones, unprecedented surveillance powers, and now, apparently, the pumping of billions of dollars into our economy.

[Reuters]

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US Considers Chinese Investment in Artificial Intelligence a National Security Threat - Gizmodo

Artificial intelligence research is still in its infancy, at least as compared to computer science in general, but the concept of unlimited computing resources is accelerating the field.

As someone with nearly unlimited computing resources at his disposal, this is something Swami Sivasubramanian, vice president of AI at Amazon Web Services, is watching play out. Last week Sivasubramanian walked GeekWire Cloud Tech Summit attendees through the array of artificial intelligence and machine-learning services that his team has developed for AWS customers and Amazons own internal services as well.

If youve been through a few tech cycles, youve already heard a lot about artificial intelligence. Much has been promised from this research field over several decades, but the enormous amount of data now moving into cloud computing services like AWS and others allows researchers like Sivasubramanian to make real breakthroughs that werent possible when data sets were scattered and siloed.

Many of these algorithms, especially like deep learning neural nets, papers were written about even two decades ago. But what has accelerated adoption of it is that we have specialized compute infrastructure, such as GPUs, specialized CPUs, FPGAs (field programmable gate arrays), you name it, he said. The combination of huge data sets and powerful computing engines is making AI concepts previously confined to science fiction a reality.

Take two AWS customers: CSPAN and the sheriffs office of Washington County in Oregon. Using the companys Rekognition image-recognition service, both were able to automate tasks that required painstaking human labor. CSPAN can now automatically identify Congresspeople speaking on the floor of the House or Senate, saving someone from having to manually annotate those videos, and Washington County is using the service to help it process photo tips when it is looking for a person of interest in an investigation.

But its still very early days for AI applications: Sivasubramanian joked that this world is about where the field of databases was when btrees were invented in the early 1970s. Thats about to change, however, as we gain a greater understanding of how AI models work and develop more sophisticated ways of training these systems to accomplish real goals.

Watch the full video of Sivasubramanians GeekWire Cloud Tech Summit talk above, and stay tuned for more highlights from the event in the days ahead.

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Amazon Web Services AI exec: How cloud computing is driving artificial intelligence breakthroughs - GeekWire

Forbes

Ethics And Artificial Intelligence With IBM Watson's Rob High - Forbes Forbes The future of technology is rooted in artificial intelligence. In order to stay ethical, transparency, proof, and trustworthiness need to be at the root of everything AI ... and more »

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Ethics And Artificial Intelligence With IBM Watson's Rob High - Forbes - Forbes

Intel (INTC) found a major customer for its inventory of Atom x5 processors and RealSense cameras. Amazon (AMZN) has chosen Intel to help it improve on its industry-leading and trendsetting product, the Alexa-powered Echo smart speaker. Copycat products from other firms are threatening the projected $10 billion revenue contribution by 2020 of Alexa AI and Amazon Echo devices.

Amazon therefore asked Intel to supply its $21 Atom x5-Z8350 processor inside the new Echo Show and Echo Look smart home assistants. The Echo Show is Amazon's equalizer to Apple's (AAPL) upcoming music-centric HomePod smart speaker. Like the HomePod, the Echo Show touts better music listening experience with its Dolby speakers.

Unlike Alphabet's (GOOG) (NASDAQ:GOOGL) Google Home and Apple HomePod, the Intel-powered Echo Show has a touchscreen 7-inch LCD display and a 5 megapixel camera. It is also capable of making voice calls to anyone with an Amazon Echo or Echo Dot device.

(Source: AMAZON)

Why Amazon Needed Intel

The original Amazon Echo speaker only used a digital media processor. Amazon opted to buy Intel's laptop-level processor, the Atom x5-Z8350, for its latest Alexa Artificial Intelligence-enhanced smart home assistant. Amazon was the pioneer of voice-controlled smart speakers, but competition from Apple and Google is forcing it to innovate outside the old voice-command focus of Alexa.

The more powerful Atom x5-z8350 SoC (System-on-Chip) transformed the Echo Show to a full-pledged computer that can stream/display information and media entertainment to people.

This is a necessary move to keep Amazon a step ahead of imitators like Google and Apple. While its rivals are still focused on voice-centric smart home assistants, Amazon is already evolving to vision computing-friendly home appliances.

What's In It For Intel

Calculating the potential benefit to Intel is easy. Amazon has a loyal army of 80-million strong Prime subscribers. They are all potential future buyers of the $229 Echo show. The original Echo sold more than 11 million units. Amazon can probably sell 10 to 20 million units of the far more advanced Echo Show every year.

Amazon is not a Shenzhen-based Chinese tablet manufacturer. I'm assuming that Intel will charge $21 for each Atom x5 processor.

$21 x 20 million units = $410 million

Getting $410 million of new business from Amazon can help on interest payments over Intel's $20.67 billion long-term debt. Further, Intel is also the processor and camera supplier for the Amazon Echo Look smart fashion assistant. The Echo Look is equipped with a Intel RealSense SR300 camera with depth-sensing technology.

(Source: Amazon)

Aside from being able to take photos and record videos, the Echo Look allows users to get fashion style recommendations from Amazons Style Check AI service. The Echo Look is a machine-learning fashion device that can appeal to women and metrosexual males. I expect Amazon to sell 5-10 million units of the Echo Look every year.

Husbands and boyfriends will likely buy the Echo Look just to accelerate their lady love's decision on what clothes/accessories to wear. I'm married. It is very annoying to waste 20-30 minutes waiting on my wife to make up her mind what she should wear just to go to the grocery store.

(Source: Amazon)

We can guesstimate that Intel charges $25 for each SR300 camera module. If Amazon can sell 8 million units of the Echo Look every year, Intel can receive another $276 million.

Other Possible Benefits From The New Partnership With Amazon

Going forward, Intel will also probably/eventually supply Atom processors for future models of Amazon Fire tablets and Fire TV products. Amazon has enabled Alexa on old and new Fire tablet models. The Alexa Voice Remote also transforms Amazon Fire TV sticks into smart digital assistants.

Amazon is now the third-largest vendor of Android tablets. Persuading Bezos to switch to Atom tablet application processors should add more to Intel's topline. Amazon's Q4 tablet sale was 5.2 million units. Amazon's Fire TV are also the second most-popular smart TV dongles in America, with 12% penetration of U.S. Wi-Fi enabled households.

Supplying RealSense cameras and Atom processors to Amazon's Alexa devices can possibly contribute $1 billion+++/year of new revenue to Intel. Furthermore, I expect Google, Lenovo (OTCPK:LNVGY), Samsung (OTC:SSNLF) to also eventually copy the Echo Show and Echo Look. They might consider using Intel Atom processors and RealSense cameras too.

Conclusion

Amazon's decision to use Atom processors and RealSense cameras is a good reason to stay long INTC. The x86 Atom may not have succeeded as a smartphone application processor, but it is now being adopted in machine-learning Internet of Things devices.

Amazon's choice of an Atom x86 processor (rather than an ARM one) for new Echo devices also helps erase the scar of Intel's ill-fated $10 billion gamble on mobile application processors.

Going forward, I hope the pricey acquisitions of Altera and Mobileye can lead to Intel getting hardware supply business for Amazon's AI cloud platform. Altera's FPGAs can compete with GPUs in parallel computing-heavy deep learning applications.

I am long INTC and AMZN. Even though my Intel exposure is notably larger, I'm not embarrassed to admit that I made more money on AMZN. Intel hitching its wagon to high-flying Amazon's Alexa star might help INTC climb higher than $38.

(Source: Google Finance)

Disclosure: I am/we are long INTC, AAPL, AMZN, GOOG.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

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Intel Is Helping Amazon Build Its Alexa Artificial Intelligence Kingdom - Seeking Alpha