Category Archives: Artificial Intelligence

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

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

Forbes

3 Steps To Embedding Artificial Intelligence In Enterprise Applications Forbes In the context of contemporary applications, it's hard to think of an application that doesn't use a database. From mobile to web to the desktop, every modern application relies on some form of a database. Some apps use flat files while others rely on ...

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3 Steps To Embedding Artificial Intelligence In Enterprise Applications - Forbes

Forbes

Emerging Artificial Intelligence (AI) Leaders: Rana el Kaliouby, Affectiva Forbes Without our emotions, we can't make smart decisions, says Rana el Kaliouby. In the field of artificial intelligence, this is sheer heresy. Isn't the goal of AI to create a machine with human-level intelligence but without the human baggage of ...

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Emerging Artificial Intelligence (AI) Leaders: Rana el Kaliouby, Affectiva - Forbes

A few years back, cloud computing transformed customer management, giving every small and medium business access to unified data and communication platforms without the need to make heavy investments in IT infrastructure and staff. This time around, the next revolution in the space is being driven by artificial intelligence algorithms that help businesses automate customer outreach and make optimal use of data.

Beneath the surface of the roiling sea of data were generating hide exceptional business and sales opportunities. But the problem is theres now more information available than limited human resources and legacy tools can handle.

Fortunately, making sense of data, both structured and unstructured, is something that artificial intelligence is becoming increasingly proficient at. While were still least decades away from human-level synthetic intelligenceAI that will match the human brain in reasoning and decision makingmachine learning algorithms, computer vision, natural language processing and generation (NLG/NLP), and other forms of narrow artificial intelligence are proving to be the best complement for human activity.

AI-powered tools are now helping scale the efforts of sales teams by gleaning useful patterns from data, finding successful courses of action, and taking care of the bulk of the work in addressing customer needs and grievances.

Main providers of Customer Relationship Management (CRM) solutions have started to invest in the added value of AI. Last year, SalesForce, the leader in the CRM industry, announced Einstein, an AI assistant that, when launched, will be omnipresent across its platform. Einstein puts its AI chops to work to continuously study the flood of data SalesForces collects from sales, e-commerce activity, emails, IoT generated data and social media streams among others. The AI engine will then make suggestions across different use cases. For instance, it helps sales reps focus on the most promising leads based on engagement data analysis, or gives advice on when to trigger email campaigns according to customer response history.

SAP, another top competitor in the field, is also joining the fray by adding AI functionalities to its S/4HANA cloud ERP. The tacked-on features will give automated insights into the business data the system collects. This includes monitoring accounts or preparing lists of top vendors for an organization based on their pricing, past performance and ability to deliver.

Oracle also declared its cloud AI project earlier this year, called Adaptive Intelligence. The initiative involves a series of add-on applications that integrate with its cloud suite. These apps combine third-party data with real-time analytics to optimize decisions and recommendations in various domains. For example, the AI Offers app merges data from the company cloud and the Oracle Data Cloud to extract contextual insights into individual customer behaviors and provide personalized offers as visitors browse websites powered by the Commerce Cloud.

Other players are focusing on verticals and optimizing specific disciplines. Growbots, a lead generation platform, uses machine learning algorithms to automate the prospecting process and marketing campaigns. The platform uses machine learning algorithms to scan websites and gather publicly available information, and enrich its database of profiles about people and businesses. Growbots incorporates this information with client CRM data to identify new potential customers and create tailored prospect lists. The platform integrates with SalesForce and uses AI to enhance and automate email marketing, creating tailored emails for customers, scheduling campaigns and sending follow ups at opportune times. The AI engine uses Natural Language Processing to parse responses and channel positive replies to the sales team.

Such solutions can be a boon to salespersons who are under constant pressure to meet quotas. By enhancing and automating the routine-based parts of the business process, AI-powered tools enable sales teams to focus on their efforts on better serving the more complicated and human-demanding needs of customers. Over time, as these solutions continue to process company and customer data, they become more efficient in their functionality.

Another example is Conversica, an AI-powered assistant that functions like a sales employee and reaches out to anyone who has shown interest in the company, such as by downloading a whitepaper or requesting information from the website. The assistant processes replies from customers, determines feedback and potential questions and crafts a meaningful reply. The assistant passes off the lead to a human salesperson when the time is right.

Another interesting development in the space is the advent of customer service chatbots, which have become more popular in recent years. Powered by AI algorithms, these bots are becoming much more efficient at independently identifying and resolving customer problems through natural conversation. These assistants free up staff time for more critical and complicated tasks.

Amelia is a virtual customer assistant that uses natural language processing to understand customer queries and provide answer based on data gathered from previous interactions and the company knowledge base. According to estimates, Amelia solves 55 percent of incidents. When it doesnt have an answer or senses a frustration or hostility, it will pass on to a human operator.

Soul Machines, a eerily named startup based in New Zealand, is creating chatbots with expressive digital faces that understand and manifest human emotion. Nadia, the first iteration of their technology, uses AI algorithms to discern human tone and facial expression. The developers believe these chatbots will eventually create a richer experience and be able to engage customers at a much more personal level.

These are some of the trends that are transforming the ways businesses interact with their customers. AI-powered customer support and management will surely result in more satisfied and less frustrated customers, and more productive sales teams. We expect to see more exciting developments in the space in the coming months.

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How artificial intelligence is revolutionizing customer management - TNW

Forbes

How Artificial Intelligence Is Revolutionizing Enterprise Software In 2017 Forbes These and many other fascinating insights are from the Cowen and Company Multi-Sector Equity Research study, Artificial Intelligence: Entering A Golden Age For Data Science (142 pp., PDF, client access reqd). The study is based on interviews with 146 ...

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How Artificial Intelligence Is Revolutionizing Enterprise Software In 2017 - Forbes

Soren Schwertfeger, centre, and his team of assistants work on an automated arm at his artificial intelligence lab in Shanghai.

Soren Schwertfeger finished his postdoctorate research on autonomous robots in Germany and seemed set to continue his work in Europe or the United States, where artificial intelligence was pioneered and established.

Instead, he went to China.

"You couldn't have started a lab like mine elsewhere," Schwertfeger said.

The balance of power in technology is shifting. China, which for years watched enviously as the West invented the software and the chips powering today's digital age, has become a major player in artificial intelligence, what some think may be the most important technology of the future. Experts widely believe China is only a step behind the United States.

China's ambitions mingle the most far-out sci-fi ideas with the needs of an authoritarian state: Philip K. Dick meets George Orwell. There are plans to use it to predict crimes, lend money, track people on the country's ubiquitous closed-circuit cameras, alleviate traffic jams, create self-guided missiles and censor the internet.

Beijing is backing its artificial intelligence push with vast sums of money. Having already spent billions on research programs, China is readying a new multibillion-dollar initiative to fund moonshot projects, start-ups and academic research, all with the aim of growing China's AI capabilities, according to two professors who consulted with the government on the plan.

China's private companies are pushing deeply into the field as well, although the line between government and private in China sometimes blurs. Baidu often called the Google of China and a pioneer in artificial-intelligence-related fields, like speech recognition this year opened a joint company-government laboratory partly run by academics who once worked on research into Chinese military robots.

China is spending more just as the United States is cutting back. This past week, the Trump administration released a proposed budget that would slash funding for a variety of government agencies that have traditionally backed artificial intelligence research.

"It's a race in the new generation of computing," said James Lewis, a senior fellow at the Centre for Strategic and International Studies. "The difference is that China seems to think it's a race and America doesn't."

For Schwertfeger, the money mattered. He received a grant six times larger than what he might have gotten in Europe or America. That enabled him to set up a full artificial intelligence lab, with an assistant, a technician and a group of PhDstudents.

"It's almost impossible for assistant professors to get this much money," he said. "The research funding is shrinking in the USand Europe. But it is definitely expanding in China."

Schwertfeger's lab, which is part of ShanghaiTech University, works on ways for machines, without aid from humans, to avoid obstacles. Decked out with wheeled robots, drones and sensors, the lab works on ways for computers to make their own maps and to improve the performance of robots with tasks like finding objects specifically, people during search-and-rescue operations.

Much of China's artificial intelligence push is similarly peaceful. Still, its prowess and dedication have set off alarms within the USdefence establishment. The Defense Department found that Chinese money had been pouring into USartificial intelligence companies some of the same ones it had been looking to for future weapons systems.

Quantifying China's spending push is difficult, because Chinese authorities disclose little. But experts say it looks to be considerable. Numerous provinces and cities are spending billions on developing robotics, and a part of that funding is likely to go to artificial intelligence research. For example, the city of Xiangtan, in China's Hunan province, has pledged $US2 billion toward developing robots and artificial intelligence. Other places have direct incentives for the AI industry. In Suzhou, leading artificial intelligence companies can get about $US800,000 in subsidies for setting up shop locally, while Shenzhen, in southern China, is offering $US1 million to support any AI project established there.

On a national level, China is working on a system to predict events like terrorist attacks or labour strikes based on possible precursors like labour strife. A paper funded by the National Natural Science Foundation of China showed how facial recognition software could be simplified so that it could be more easily integrated with cameras across the country.

China is preparing a concerted nationwide push, according to the two professors who advised on the effort but declined to be identified, because the effort had not yet been made public. While the size wasn't clear, they said, it would most likely result in billions of dollars in spending.

Trump's proposed budget, meanwhile, would reduce the National Science Foundation's spending on intelligent systems by 10 per cent, to about $US175 million. Research and development in other areas would also be cut, although the proposed budget does call for more spending on defence research and some supercomputing. The cuts would essentially shift more research and development to private UScompanies like Google and Facebook.

"The previous administration was preparing for a future with artificial intelligence," said Subbarao Kambhampati, president of the Association for the Advancement of Artificial intelligence. "They were talking about increasing basic research for artificial intelligence. Instead of increases, we are now being significantly affected."

China's money won't necessarily translate into dominance. The government's top-down approach, closed-mouth bureaucracy and hoarding of information can hobble research. It threw a tremendous amount of resources toward curing severe acute respiratory syndrome, the deadly virus known as SARS, when it swept through the country 15 years ago. Yet the virus was eventually sequenced and tamed by a small Canadian lab, said Clay Shirky, a professor at NYU Shanghai and a technology writer.

"It wasn't that anyone was trying to stop the development of a SARS vaccine," Shirky said. "It's the habit that yes is more risky than no."

Authorities in China are now bringing top-down attention to fixing the problem of too much top-down control. While that may not sound promising, Wang Shengjin, a professor of electronic engineering at China's Tsinghua University, said he had noticed some improvement, such as professional groups sharing information, and authorities who are rolling back limits on professors claiming ownership of their discoveries for commercial purposes.

"The lack of open sources and sharing of information, this has been the reality," Wang said. "But it has started to change."

At the moment, cooperation and exchanges in artificial intelligence between the United States and China are largely open, at least from the USside. Chinese and USscholars widely publish their findings in journals accessible to all, and researchers from China are major players in USresearch institutions.

Chinese tech giants like Baidu, Tencent and Didi Chuxing have opened artificial intelligence labs in America, as have some Chinese start-ups. Over the past six years, Chinese investors helped finance 51 USartificial intelligence companies, contributing to the $US700 million raised, according to the recent Pentagon report.

It's unclear how long the cooperation will continue. The Pentagon report urged more controls. And while there are government and private pushes out of China, it is difficult to tell which is which, as Baidu shows.

Baidu is a leader in China's artificial intelligence efforts. It is working on driverless cars. It has turned an app that started as a visual dictionary take a picture of an object, and your cellphone will tell you what it is into a site that uses facial recognition to find missing people, a major problem in a country where child kidnapping has been persistent. In one stunning example, it helped a family find a child kidnapped 27 years earlier. DNA testing confirmed the family connection.

Baidu's speech-recognition software which can accomplish the difficult task of hearing tonal differences in Chinese dialects is considered top of the class. When Microsoft announced last October that its speech recognition software had surpassed human-level language recognition, Baidu's head of research at the time playfully reminded the UScompany that his team had accomplished a similar feat a year earlier.

In an apparent effort to harness Baidu's breakthroughs, China said this year that it would open a lab that would cooperate with the company on AI research. The facility will be headed by two professors with long experience working for government programs designed to catch up to and replace foreign technology. Both professors also worked on a program called the Tsinghua Mobile Robot, according to multiple academic papers published on the topic. Research behind the robot, which in one award is described as a "military-use intelligent ground robot", was sponsored by funding to improve Chinese military capabilities.

Li Wei, a professor involved in the Baidu cooperative effort, spent much of his career at Beihang University, one of China's seven schools of national defense.

A company spokeswoman said: "Baidu develops products and services that improve people's lives. Through its partnership with the AI research community, Baidu aims to make a complicated world simpler through technology."

Still, there are advantages in China's developing cutting-edge AI on its own. National efforts are aided by access to enormous amounts of data held by Chinese companies and universities, the large number of Chinese engineers being trained on either side of the Pacific and from government backing, said Wang, of Tsinghua.

Driving that attention is a breakthrough from a UScompany largely banned in China: Google. In March 2016, a Google artificial intelligence system, AlphaGo, beat a South Korean player at the complicated strategy game Go, which originated in China. This past week, AlphaGo beat the best player in the world, a Chinese national, at a tournament in Wuzhen, China.

The Google event changed the tenor of government discussions about funding, according to several Chinese professors.

"After AlphaGo came out and had such a big impact on the industry," said Zha Hongbin, a professor of machine learning at Peking University, "the content of government discussions got much wider and more concrete."

Shortly afterward, the government created a new project on brain-inspired computing, he added.

For all the government support, advances in the field could ultimately backfire, Shirky said. Artificial intelligence may help China better censor the internet, a task that often blocks Chinese researchers from finding vital information. At the same time, better AI could make it easier for Chinese readers to translate articles and other information.

"The fact is," Shirky said, "unlike automobile engineering, artificial intelligence will lead to surprises. That will make the world considerably less predictable, and that's never been Beijing's favourite characteristic."

Additional research by Carolyn Zhang in Shanghai

The New York Times

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China is outsmarting America in artificial intelligence - The Australian Financial Review

The recent technological advancement within artificial intelligence, the "Internet of Things", and robotics has generated significant impact on traditional businesses, causing decreasing profit margins across several sectors, whereas most of the big winners in the Wall Street IPOs are companies with innovative ideas from Facebook (NASDAQ: FB) and Twitter, (NASDAQ: TWTR) to Snapchat (NYSE: SNAP). There are two common determining factors among those successful IPOs: Ideation and User Generated Content (UGC).

In the era of big data and artificial intelligence, we will soon be able to create the tools to better capture the value from ideation and UGC, as well as spur economic growth by capitalizing on human ingenuity. With the ever-accelerating developments in technology, the world is in the process of moving from a consumer economy to a knowledge-based economy, and from a debt- based system to an equity based system, which will include movement from tangible assets to intangible assets. Hence we envision that our world economic system will operate on a new growth formula.

This growth formula is as follows:

IA > M1 IC + AI = W

which translate into Intangible Assets (IA) is greater than Money Supply ((M1)) - therefore - Intellectual Capital (IC) plus Artificial Intelligence (AI) equals Wealth (W).

With this formula, we are developing a new financial platform - The Artificial Intelligence Economic Development Corporation (AIEDC). This platform will combine artificial intelligence with human intelligence along with big data to spur long term sustainable economic development that will facilitate the discovery, as well as the advancement of ideas - from ideation to monetization, in the area of economic development through the creation of new businesses, land infrastructure projects, environmental projects, scientific research, and technological projects.

At this time, the AI community is very vibrant and open with a lot of open source projects pioneered by the likes of companies such as, Google (NASDAQ: GOOG), Facebook and Amazon (NASDAQ: AMZN). These open source projects will be extremely beneficial to the future of growth and economic development of the World.

The high performance computing technology which is quantum leaping at this time, has been fueled by the recent developments in bitcoin mining, as well as the new chips that are being released every month, such as the tensor processing unit (TPU) from Google and Volta architecture from Nvidia (NASDAQ: NVDA) that are taking AI development to the next level.

According to Accenture LLP's report "Why Artificial intelligence is The Future of Growth", research on the impact of AI in 12 developed economies reveals that AI could double annual economic growth rates by 2035, specifically by changing the nature of work and creating a new relationship between Man and Machine. The impact of AI technologies on businesses is projected to increase labor productivity by up to 40 percent and enable people to make more efficient use of their time. This additional allocation of "Time" will further seed the development of ideation and user generated content.

Government organizations around the world have been accumulating vast amounts of data - by forming public private partnerships (P3's), AIEDC's platform will help governments all over the world through strategic partnerships for economic development.

At the center of the company will reside the M.I.N.D - a Machine Intelligence Neural-Network Database. Our neural network database is a clustered computational model with artificial neurons receiving input variables similar to a biological brain in a human being. The database will be the collective sum of all the data being fed into the M.I.N.D at that time.

The M.I.N.D. enabled platform will utilize artificial intelligence to combine the aspects of incubators, venture capital firms, crowdfunding, as well as project financing. It will include, but not be limited to intellectual property registration and protection, blockchain based smart contracts, and initial cryptocurrency offerings.

Finally, the M.I.N.D. will convert the Ideas submitted by users from intellectual capital to intellectual property.

With this platform, people with innovative ideas will be able to have their ideas validated, protected and converted into capital; investors will have a new platform and mechanism to effectively invest in new ideas and or companies; industry practitioners will have more and better ideas to execute on; governments will have additional income through their stake in the platform funded projects; the society will have a long term sustainable growth model.

Here are some thoughts from industry visionaries:

DeepMind's Cofounder Mustafa Suleyman:

The following is from the Business Insider article, 'In many areas, capitalism is currently failing us'

"And yet in many areas, capitalism is currently failing us," he said. "We actually need a new kind of set of incentives to tackle some of most pressing and urgent social problems and we need a new kind of tool, a new kind of intelligence, that is distributed, that is scaled, that is accessible, to try and make sense of some of the complexity that is overwhelming us."

Facebook's Cofounder Eduardo Saverin: stated the following as well:

This quote is taken from a CNBC article title, What I Learned From Watching "The Social Network"

"Entrepreneurship involves mistakes and failures. But ultimately, if you have that intellectual capital and intimate understanding behind your project, you have a chance to succeed. Intellectual capital, and not just monetary capital, will spawn the next great product or idea. Entrepreneurs, especially in the technology sector, will create things tomorrow that we can barely imagine today".

Leonard S. Johnson, The Artificial Intelligence Economic Development Corporation.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

Business relationship disclosure: I am the CEO of the Artificial Intelligence Economic Development Corporation

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The Future Of Growth And Economic Development Powered By Human And Artificial Intelligence - Seeking Alpha

Sophia, a human-like robot, being interviewed during the AI for Global Good Summit in Geneva, Switzerland. Photo by: International Telecommunication Union/ CC BY

Perhaps the most photographed individual at the AI for Global Good Summitin Geneva, Switzerland, last week was not a human but a humanoid called Sophia.

As I get smarter, I hope to understand people better help you, work with you as a friend, to imagine and build a better future for us all, Sophia, an uncannily human-like robot, said in a Facebook Liveinterview.

In that interview and onstage at the summit, her eyebrows lifted, she smiled gently, and her eyes lit up as she answered questions from the audience, with moments where only the glimpse of cords behind her face revealed that she is a machine.

Hanson Robotics developed Sophia as part of its mission to create genius machines that live and love, and work together with humans to build a a smarter and better future. Her creator, Dr. David Hanson, appeared alongside Sophiaat the summit, presenting her as an example of his work to develop robots that can learn creativity, empathy and compassion. These are the traits he thinks must be combined with artificial intelligence so that robots can solve problems too complex for people to solve on their own.

Sophias appearance placed her amongst some of the leading minds across academia and industry who are helping humanitarian agencies examine how AI can help meet global goals.

Discussions centered around how AI is already changing the world, ways to harness the technologys potential for good, and challenges ranging from policy to security to privacy in advancing the contributions of AI to the Sustainable Development Goals. Sessions explored applications of AI, including advancing the personalization of education, augmenting medical practice and health care policy, and improving smart cities. The event was convened by the XPRIZE Foundationand the United Nations International Telecommunications Unionin partnership with 20 U.N. agencies.

How artificial intelligence might help achieve the SDGs

Global development professionals are working on complex problems that might appeal to machine learning experts looking to use their artificial intelligence skills for good. A growing number of efforts are bringing these communities together.

Artificial Intelligence has the potential to accelerate progress towards a dignified life, in peace and prosperity, for all people, saidU.N. Secretary-General Antnio Guterres. The time has arrived for all of us governments, industry and civil society to consider how AI will affect our future.

The summit represents the beginnings of the U.N.s efforts to ensure advances in AI can benefit all of humanity,he said. The event was part of a broader conversation as a number of actors in the development community are looking at how AI could augment their work, for example by helping organizations to analyze and act upon the enormous volumes of data they are collecting.

Last week, chief strategy officers gathered for the World Economic Forums Industry Strategy Meetingin San Francisco asked whether AI needs a Hippocratic oath, and discussed ways to train computer scientists to understand the ethical implications of the technologies they are developing.

I actually find it hard to name a major industry that I dont think AI can transform in the next several years.

Industry experts predict that AI could have a huge disrupting effect, with all the benefits and risks that follow.

AI is the new electricity, Andrew Ng, one of the leading thinkers on artificial intelligence, told Devex at a recent eventat Stanford University on the role of AI in achieving the SDGs. I actually find it hard to name a major industry that I dont think AI can transform in the next several years.

Ng is the co-founder of the education technology company Coursera, having recently led the AI efforts at Baidu, the Chinese search engine, and at Google, where he founded and led the Google Brain project, developing deep learning algorithms. Now he says he wants to advance AI beyond the tech world.

The most obvious cases for AI use include anything a typical human can do in less than a second of thought, he said. Image recognition is one common example, but AI also has powerful applications in education and health care in both the developed and developing world, said Ng.

We believe that AI is a transformative platform that will improve everything, Zenia Tata, executive director of global development at XPRIZE, told Devex via email. As such, the implications for development professionals are huge. Whether you are working in health care, water quality, market access for smallholder farmers or financial services for the underserved, AI will help you do it better in so many ways, as an example it will help with rapidly analyzing data and create predictive models.

As they have done with other technologies, developing countries may be able to leapfrog with some AI applications, because there are fewer regulatory barriers there for entrepreneurs looking to test these technologies, Ng said.

Yet while developing countries stand to benefit, they also face the greatest risk of being left behind, Guterres of the U.N. said.

One of the sessions at the summit in Geneva centered around promoting equality in access to AI. Discussions centered around how to ensure access to potential beneficial applications, such as diagnosing disease or promoting democracy.

Among the risks going forward will be the potential impact on the labor force. Several speakers at the AI for Global Good summit urged policymakers to begin preparing the workforce for new jobs in a future that is about human machine collaboration.

Technologists such as Ng have argued for the need to rethink social safety nets, and his preferred option is a conditional basic income, through which people are paid if they are unemployed, with the expectation that they study.

The global development community can be a strong partner in working to ensure that AI benefits everyone, said Ruchit Garg, the founder of Harvesting, which applies AI techniques to satellite imagery to drive financial inclusion for farmers.

This starts with understanding what AI is, how this may or may not work for various sections of society in different settings, creating platforms like this global summit to create dialogue between relevant global players, and finally facilitating standards and guidelines for industry to adopt which can ensure development of AI in [a way that] brings good to humanity in inclusive way, he said.

There is a precedent, he said: The ITU helped define telecommunications industry standards such as 3G, 5G, and Long Term Evolution. The organization could play a similar role in standardizing AI.

Christopher Fabian of UNICEFsaid in an interview at the summitthat he hopes to see development organizations launch partnerships with technology companies, as UNICEF has done with drones and UAVs, to move from conversation to action on AI for good.

If we can help to define some of the greatest needs in the world, and also a path to profit, how business can be involved with those needs, he said, we can create both more consistent and solid businesses but also help those who most need it.

Read more international development newsonline, and subscribe to The Development Newswireto receive the latest from the worlds leading donors and decision-makers emailed to you free every business day.

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Artificial Intelligence for Good sees development applications | Devex - Devex

None of us is as wise as all of us, when it comes to diagnostics. So it makes sense to involve deep learning in medicine wherever we can. Think of what IBMs Watson can do today. Now imagine an AI capable of deep learning one specifically built for medicine, programmed for diagnostics. Any one person isnt going to win when pitched against the assembled diagnostic insights and clinical pearls of all the doctors, past and present. Put another way, deep learning could be an incredible force multiplier.

And we need all the force multipliers we can get, in this unending war against disease. Build a better mousetrap, as the saying goes, and Nature will build a better mouse. Sure enough, diseases evolve. Even viruses. As you may know, there are multiple strains of HIV? Group M is just one type of the first strain (HIV-1) responsible for the human AIDS pandemic. But there are about a dozen subtypes within group M that each hang out in their own bioregion.

One of the obstacles to treating HIV is its high genetic variability. Its difficult to make antibody-based drugs fast enough to keep up with a virus thats constantly shuffling around its genome. Trials for a vaccine are ongoing, but nobody has quite got it, partly because of this incessant mutation.

The fascinating thing about viruses is that under the hood theyre nothing but a wisp of genetic material, with a header and footer containing its duplication code, plus a few lines of metadata that might code for a protein or a lipid or two. Just like you can track changes in Word, you can track changes in a virus over time, given enough samples and sufficient investment of computational muscle. Thats how we know about all those subtypes.

HIV attacking red blood cells

As it happens, though, multivariate analysis is a particular strength of AI. The kind of sophisticated n-dimensional number crunching that could keep a team of dozens of scientists busy for years, Watson could eat for breakfast with its 16 terabytes of RAM. Thats how we get those beautiful predictive models of what galaxies will do when they collide, and how the aerodynamic performance will work on a car designed entirely with CAD.

Its also what makes AI a powerful ally in the fight against HIV.

Many factors govern the spread of diseases. Beyond the pathogens own genetic sequence, and the virulence factors it codes for, there are still many other variables. Economic, political, social, and meteorological forces can change the movement of people, individually and en masse. There is a nationwide opiate and heroin addiction crisis, and in its wake there is a gathering storm of HIV infections via needle sharing. People move around the planet, and with those people travel the pathogens they host.

But we could use AI to construct a nuanced, informed assessment of many different such forces and factors, by plugging in that ridiculous volume of multivariate data to a program that can track all those changing rates at once. We could deploy deep learning and neural nets to suss out the patterns we cant see, and then use those patterns to track and predict the spread and change of the many subtypes of HIV.

But the AIs work isnt done yet. Comparing the change in genetic code with infection rates and virulence factors could give us a better model for working toward a vaccine for this insufferable virus. And if we finally managed to program an AI that would tell us how it arrives at its conclusions, that would be a powerful collaboration indeed. Imagine an AI that evolves with the virus it tracks. A purpose-built artificial intelligence that could tell us how its making its decisions, if applied to epidemiology and virology, could advance the entire field.

Excerpt from:

How to Apply Artificial Intelligence to the HIV/AIDS Pandemic - ExtremeTech