Daily Archives: July 19, 2017

If you hadnt heard, Elon Musk is worried about the machines.

Though that may seem a quixotic stance for the head of multiple techcompanies to take, it seems that his proximity to the bleeding edge of technological development has given him the heebie-jeebies when it comes to artificial intelligence. Hes shared his fears of AI running amok before, likening it to summoning the demon, and Musk doubled down on his stanceat a meeting of the National Governors Association this weekend, telling state leaders that AI poses an existential threat to humanity.

Amid a discussion of driverless vehicles and space exploration, Musk called for greater government regulations surrounding artificial intelligence research and implementation, stating:

Until people see robots going down the street killing people, they dont know how to react because it seems so ethereal. AI is a rare case where I think we need to be proactive in regulation instead of reactive. Because I think by the time we are reactive in AI regulation, its too late, according to theMIT Tech Review.

Its far from delusional to voice such concerns, given that AI could one day reach the point where it becomes capable of improving upon itself, sparking a feedback loop of progress that takes it far beyond human capabilities. When well actually reach that point is anyones guess, and were not at all close at the moment, as todays footage of a security robot wandering blindly into a fountain makes clear.

While computers may be snapping up video game records and mastering poker, they cannot approximate anything like general intelligence the broad reasoning skills that allow us to accomplish many variable tasks. This is why AI that excels at a single task, like playing chess, fails miserably when asked to do something as simple as describe a chair.

To get some perspective on Musks comments,Discover reached out to computer scientists and futurists working on the very kind of AI that the tech CEO warns about.

Elon Musks obsession with AI as an existential threat for humanity is a distraction from the real concern about AIs impact on jobs and weapons systems. What the public needs is good information about the actual consequences of AI both positive and negative. We have to distinguish between science and science fiction. In fictional accounts, AI is often cast as the bad guy, scheming to take over the world, but in reality AI is a tool, a technology and one that has the potential to save many lives by improving transportation, medicine, and more. Instead of creating a new regulatory body, we need to better educate and inform people on what AI can and cannot do. We need research on how to build AI guardiansAI systems that monitor and analyze other AI systems to help ensure they obey our laws and values. The world needs AI for its benefits, AI needs regulation like the Pacific ocean needs global warming.

Elon Musks remarks arealarmist. I recently surveyed300 leading AI researchers andthe majority of themthinkit will take at least 50 moreyearsto get tomachines as smart as humans. Sothis is not a problem that needs immediate attention.

And Im not too worried about what happenswhen we get to super-intelligence, astheresa healthy research communityworking onensuring that thesemachines wont pose an existential threat to humanity. I expecttheyll have worked out preciselywhat safeguards are needed by then.

But Elon is right about one thing: We do need government to startregulating AI now.However, it isthe stupid AI we have today that we need to start regulating.The biased algorithms. Thearms race to develop killer robots, where stupid AI will be giventhe ability to make life or death decisions. The threat to our privacy as the techcompanies get hold of all our personal and medical data. And the distortionof political debate that the internet is enabling.

The tech companies realizethey have a problem, and they havemade some efforts to avoid government regulation by beginning toself-regulate.Butthere are serious questions to be askedwhether they can be left to do this themselves.We are witnessing anAI race between the big tech giants, investing billionsof dollars in thiswinner takes all contest. Many other industries have seengovernment step in to prevent monopolies behaving poorly. Ive said thisin a talk recently, but Ill repeat it again: If some of the giants like Google and Facebookarent broken up in twenty years time, Ill be immensely worried for thefuture of our society.

There are no independent machine values; machine values are human values. If humanity is truly worried about the future impact of a technology, be it AI or energy or anything else, lets have all walks and voices of life be represented in developing and applying this technology. Every technologist has a role in making benevolent technology for bettering our society, no matter if its Stanford, Google or Tesla. As an AI educator and technologist, my foremost hope is to see much more inclusion and diversity in both the development of AI as well as the dissemination of AI voices and opinions.

Artificial Intelligence is already everywhere. Its ramifications of use rival that of the Internet,and actually reinforces them. AIis being embedded in almost every algorithm and system were building now and in the future. There is an essential opportunity to prioritize ethical and responsible design today for AI. However, this is more related to the greater immediate risk for AI and society, which isthe prioritization of exponential economic growth while ignoring environmental and societal issues.

In terms of whether Musks warnings of existential threats regarding Artificial Super-intelligence merit immediate attention, we actually risk large-scale negative and unintended consequences because were placing exponential growth and shareholder value abovesocietal flourishing metricsas indicators of successfor these amazing technologies.

To address these issues, every stakeholder creating AI must address issues of transparency, accountability and traceability in their work. They must ensure the safe and trusted access to and exchange of user data as encouraged by the GDPR (General Data Protection Regulation)in the EU. And they must prioritize human rights-centric well being metrics like the UN Sustainable Development Goals as predetermined global metrics of success that can provably increase human prosperity.

TheIEEE Global AI Ethics InitiativecreatedEthically Aligned Design: A Vision for Prioritizing Human Wellbeing with Artificial Intelligence and Autonomous Systemsto pragmatically help any stakeholders creating these technologies toproactively deal with the general types of ethical issues Musks concerns bring up. The group of over 250 global AI and Ethics experts were also the inspiration behind the series ofIEEE P7000 Standards Model Process for Addressing Ethical Concerns During System Designcurrently in progress, designed to create solutions to these issues in a global consensus building process.

My biggest concern about AI is designing and proliferating the technology without prioritizing ethical and responsible design or rushing to increase economic growth in a time we so desperately need to focus on environmental and societal sustainability to avoid the existential risks weve already created without the help of AI. Humanity doesnt need to fear AI, as long as we actnowto prioritize ethical and responsible design of it.

Elon Musks concerns about AI that will pose an existential threat to humanity are legitimate and should not be dismissedbut they concern developments that almost certainly lie in the relatively far future, probably at least 30 to 50 years from now, and perhaps much more.

Calls to immediately regulate or restrict AI development are misplaced for a number of reasons, perhaps most importantly because the U.S. is currently engaged in active competition with other countries, especially China. We cannot afford to fall behind in this critical race.

Additionally, worries about truly advanced AI taking over distract us from the much more immediate issues associated with progress in specialized artificial intelligence. These include the possibility of massive economic and social disruption as millions of jobs are eliminated, as well as potential threats to privacy and the deployment of artificial intelligence in cybercrime and cyberwarfare, as well as the advent of truly autonomous military and security robots. None of these more near term developments rely on the development of the advanced super-intelligence that Musk worries about. They are a simple extrapolation of technology that already exists. Our immediate focus should be on addressing these far less speculative risks, which are highly likely to have a dramatic impact within the next two decades.

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Artificial Intelligence Experts Respond to Elon Musk's Dire Warning for US Governors - Discover Magazine (blog)

As an artificial intelligence researcher, I often come across the idea that many people are afraid of what AI might bring. Its perhaps unsurprising, given both history and the entertainment industry, that we might be afraid of a cybernetic takeover that forces us to live locked away, Matrix-like, as some sort of human battery.

And yet it is hard for me to look up from the evolutionary computer models I use to develop AI, to think about how the innocent virtual creatures on my screen might become the monsters of the future. Might I become the destroyer of worlds, as Oppenheimer lamented after spearheading the construction of the first nuclear bomb?

I would take the fame, I suppose, but perhaps the critics are right. Maybe I shouldnt avoid asking: As an AI expert, what do I fear about artificial intelligence?

Oper proprie, CC BY-SA

The HAL 9000 computer, dreamed up by science fiction author Arthur C. Clarke and brought to life by movie director Stanley Kubrick in 2001: A Space Odyssey, is a good example of a system that fails because of unintended consequences. In many complex systems the RMS Titanic, NASAs space shuttle, the Chernobyl nuclear power plant engineers layer many different components together. The designers may have known well how each element worked individually, but didnt know enough about how they all worked together.

That resulted in systems that could never be completely understood, and could fail in unpredictable ways. In each disaster sinking a ship, blowing up two shuttles and spreading radioactive contamination across Europe and Asia a set of relatively small failures combined together to create a catastrophe.

I can see how we could fall into the same trap in AI research. We look at the latest research from cognitive science, translate that into an algorithm and add it to an existing system. We try to engineer AI without understanding intelligence or cognition first.

Systems like IBMs Watson and Googles Alpha equip artificial neural networks with enormous computing power, and accomplish impressive feats. But if these machines make mistakes, they lose on Jeopardy! or dont defeat a Go master. These are not world-changing consequences; indeed, the worst that might happen to a regular person as a result is losing some money betting on their success.

But as AI designs get even more complex and computer processors even faster, their skills will improve. That will lead us to give them more responsibility, even as the risk of unintended consequences rises. We know that to err is human, so it is likely impossible for us to create a truly safe system.

Im not very concerned about unintended consequences in the types of AI I am developing, using an approach called neuroevolution. I create virtual environments and evolve digital creatures and their brains to solve increasingly complex tasks. The creatures performance is evaluated; those that perform the best are selected to reproduce, making the next generation. Over many generations these machine-creatures evolve cognitive abilities.

Right now we are taking baby steps to evolve machines that can do simple navigation tasks, make simple decisions, or remember a couple of bits. But soon we will evolve machines that can execute more complex tasks and have much better general intelligence. Ultimately we hope to create human-level intelligence.

Along the way, we will find and eliminate errors and problems through the process of evolution. With each generation, the machines get better at handling the errors that occurred in previous generations. That increases the chances that well find unintended consequences in simulation, which can be eliminated before they ever enter the real world.

Another possibility thats farther down the line is using evolution to influence the ethics of artificial intelligence systems. Its likely that human ethics and morals, such as trustworthiness and altruism, are a result of our evolution and factor in its continuation. We could set up our virtual environments to give evolutionary advantages to machines that demonstrate kindness, honesty and empathy. This might be a way to ensure that we develop more obedient servants or trustworthy companions and fewer ruthless killer robots.

While neuroevolution might reduce the likelihood of unintended consequences, it doesnt prevent misuse. But that is a moral question, not a scientific one. As a scientist, I must follow my obligation to the truth, reporting what I find in my experiments, whether I like the results or not. My focus is not on determining whether I like or approve of something; it matters only that I can unveil it.

Being a scientist doesnt absolve me of my humanity, though. I must, at some level, reconnect with my hopes and fears. As a moral and political being, I have to consider the potential implications of my work and its potential effects on society.

As researchers, and as a society, we have not yet come up with a clear idea of what we want AI to do or become. In part, of course, this is because we dont yet know what its capable of. But we do need to decide what the desired outcome of advanced AI is.

One big area people are paying attention to is employment. Robots are already doing physical work like welding car parts together. One day soon they may also do cognitive tasks we once thought were uniquely human. Self-driving cars could replace taxi drivers; self-flying planes could replace pilots.

Instead of getting medical aid in an emergency room staffed by potentially overtired doctors, patients could get an examination and diagnosis from an expert system with instant access to all medical knowledge ever collected and get surgery performed by a tireless robot with a perfectly steady hand. Legal advice could come from an all-knowing legal database; investment advice could come from a market-prediction system.

Perhaps one day, all human jobs will be done by machines. Even my own job could be done faster, by a large number of machines tirelessly researching how to make even smarter machines.

In our current society, automation pushes people out of jobs, making the people who own the machines richer and everyone else poorer. That is not a scientific issue; it is a political and socioeconomic problem that we as a society must solve. My research will not change that, though my political self together with the rest of humanity may be able to create circumstances in which AI becomes broadly beneficial instead of increasing the discrepancy between the one percent and the rest of us.

There is one last fear, embodied by HAL 9000, the Terminator and any number of other fictional superintelligences: If AI keeps improving until it surpasses human intelligence, will a superintelligence system (or more than one of them) find it no longer needs humans? How will we justify our existence in the face of a superintelligence that can do things humans could never do? Can we avoid being wiped off the face of the Earth by machines we helped create?

If this guy comes for you, how will you convince him to let you live? tenaciousme, CC BY

The key question in this scenario is: Why should a superintelligence keep us around?

I would argue that I am a good person who might have even helped to bring about the superintelligence itself. I would appeal to the compassion and empathy that the superintelligence has to keep me, a compassionate and empathetic person, alive. I would also argue that diversity has a value all in itself, and that the universe is so ridiculously large that humankinds existence in it probably doesnt matter at all.

But I do not speak for all humankind, and I find it hard to make a compelling argument for all of us. When I take a sharp look at us all together, there is a lot wrong: We hate each other. We wage war on each other. We do not distribute food, knowledge or medical aid equally. We pollute the planet. There are many good things in the world, but all the bad weakens our argument for being allowed to exist.

Fortunately, we need not justify our existence quite yet. We have some time somewhere between 50 and 250 years, depending on how fast AI develops. As a species we can come together and come up with a good answer for why a superintelligence shouldnt just wipe us out. But that will be hard: Saying we embrace diversity and actually doing it are two different things as are saying we want to save the planet and successfully doing so.

We all, individually and as a society, need to prepare for that nightmare scenario, using the time we have left to demonstrate why our creations should let us continue to exist. Or we can decide to believe that it will never happen, and stop worrying altogether. But regardless of the physical threats superintelligences may present, they also pose a political and economic danger. If we dont find a way to distribute our wealth better, we will have fueled capitalism with artificial intelligence laborers serving only very few who possess all the means of production.

Arend Hintze, Assistant Professor of Integrative Biology & Computer Science and Engineering, Michigan State University

This article was originally published on The Conversation. Read the original article.

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What an Artificial Intelligence Researcher Fears About AI - Government Technology

A common criticism of the recent election has been that the campaigns failed to address many of the big issues that will affect the futures of most people.

Its a fair point. I dont recall hearing one politician talk about the rapidly changing world of business and work, and what this country may look like in the future or indeed what they intend to do about it.

As someone who works in the field of artificial intelligence (AI), you would expect me to pay close attention to political statements on such things. But my interest in what national leaders think is not purely a commercial one. I truly believe that AI can change our world for the better.

Read more: Meet the pair preparing London (and the world) for our AI future

However, despite its vast potential, I believe there is a key component which would allow AI to take off that is currently lacking and that is strategic ambition.

I have read frequently, including in these pages, that we are supposedly on the brink of a Fourth Industrial Revolution. But you would not know this from the way that many in government are speaking.

Two cross-party groups have recently been formed on the subject of AI, and that is encouraging. But given the silence from Whitehall and Downing Street, I am forced to wonder whether their work is being taken seriously.

The simple truth is that the UK will not be able to lead and certainly not change the world without a clear national strategy.

I ask you to consider the Space Race for a moment. This was a period of international technological innovation that spurred many of the things that we take for granted today from powerful computers and commercial flights, to satellite television and non-stick frying pans.

There was a clear objective: get into space and land on the moon. That entailed exploiting the latest technology to get there first. This competition stimulated the United States and Russia to strive for technological breakthroughs.

The result was that the Space Race opened a new era in technology, fuelling innovations that have improved the daily lives of millions of people. AI can do the same today.

It is time for the UK to shoot for the moon. That way it can and will be a leader in this new landscape. If it does not, it will merely be a guest at someone elses party.

The government urgently needs to start thinking about not just how to improve what we do already, but about what we can do differently. It needs to set out its strategic vision for a new society, taking into account automation, the gig economy, and the increasingly interconnected nature of work.

This isnt about how we confront the difficulties of developing AI its about how we use AI to solve the problems facing our country, supporting the economy and improving lives in the process. These are challenges that require a new type of intelligence.

What is intelligence? Intelligence is using knowledge effectively.

Through technology we now have a wealth of knowledge that we did not have before. We have data, vast amounts of it. But what we have often lacked so far is a way of making it useful.

AI is the key to making that knowledge useful.

Government departments sit on information that provides the clues to how society ticks. The data is there on our health, the benefits we draw upon, the types of transport we take, and the taxes we pay.

In isolation, this information is only useful to the department that holds it. But if aggregated and integrated in the right way, it can create intelligent solutions to societys problems.

A country that wants to lead in this area needs a software platform to bring the datasets together. It needs the right people who know to ask the data the right questions, and the right AI to provide them with answers.

Britain needs to be clear and united on what it wants AI to achieve so that it can make the most of the data it has at its disposal. This may sound obvious, but often governments create a policy for a perceived problem, then look for data to prove that policy will work.

In addition, the government needs to design a regulatory framework that sets out the rules of engagement for developing AI solutions that benefit society.

Ideally we want a framework that drives us all towards a common goal of making business and public services function better, and confronts concerns about privacy and data security that prevent people from embracing AIs potential.

If we act fast, and all pull in the same direction, this is an area in which UK can really shoot for the moon.

Read more: Artificial intelligence could boost the UK's household spending power

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Artificial intelligence is our chance to shoot for the moon - City A.M.

There are plenty of companies you could choose from if you wanted to benefit from the growing artificial intelligence (AI) market. I won't get into all of them, but it's safe to say that nearly all the big players in the tech sector -- like Apple, Microsoft, IBM, Intel, Facebook, and a slew of others -- believe AI could reach a market size of $59.8 billion by 2025.

But that's not helpful if you want to know which companies are making the biggest moves in the space, and which have the most potential to benefit. To help answer that, we need to take a closer look at NVIDIA Corporation (NASDAQ:NVDA) and Alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL). These companies may differ in their approach to AI, but both deserve to be at the top of the list for AI investments. Here's why.

Image source: Getty Images.

NVIDIA is basically a tech investor's dream at the moment, mainly because its share price has gained more than 200% over the past 12 months. NVIDIA makes graphics processors that are used in computers for things like high-performance gaming, but the company has been taking its graphics processing unit (GPU) know-how and wisely applying it to AI businesses as well.

For example, the company has built a self-driving supercomputer, called Drive PX 2, that processes a massive amount of image information so that semi-autonomous cars can perceive the world around them. Audi, Toyota, Tesla, and others are already using the company's AI tech for their semi-autonomous vehicles, and NVIDIA believes its total addressable market for AI-powered self-driving cars is about $8 billion 2025.

In fact, NVIDIA believes that its total addressable market for all AI will be around $40 billion between 2020 and 2025. That includes everything from self-driving cars to AI cities and GPU-powered deep-learning data centers.

The company's data-center segment is a growing AI opportunity because more and more companies are looking to GPUs to power intense image processing on their servers. Goldman Sachs analyst Toshiya Hari thinks the company already holds nearly 90% of the market for chips used for computer-training tasks, a part of the machine-learning and AI markets.

One thing investors should know is that NVIDIA's "top AI stock" designation comes from the company's potential in the space, and not necessarily from its current revenues. In fiscal first-quarter 2018, the company brought in just 7% of its total revenues from the automotive market (which includes its Drive PX system) and about 21% from its data-center business. Meanwhile, GPU sales for gaming accounted for about 53% of revenue.

But the potential here for NVIDIA is too large to ignore. Graphics processing is an integral part of many AI learning systems, and NVIDIA's chips are some of the best in the business. With automakers already betting on the company's AI computer and tech companies looking to NVIDIA for their AI data centers, it's only a matter of time before the company's AI revenues follow its opportunities.

Like NVIDIA, Alphabet is pursuing AI in several different ways, but one of the most important is using it to serve up better ads to its users.

Alphabet's Google debuted its Smart Bidding learning system last year, which uses machine learning to better automate bids on AdWords and DoubleClick. Google said at the time that the system accounts for many more factors than a person or team could determine, in order to make ads more efficient. The importance of serving up the most relevant ads becomes clear when you consider that Google is expected to earn about 78% of all U.S. search ad revenue this year, and more than 80% by 2019, according to data from eMarketer.

But Google has been very persistent in expanding its AI footprint in other areas as well. According to Recode, the company has acquired at least 20 AI companies over the past few years. One of those is DeepMind, which Google plans to use to do things like cure diseases, and find new ways for companies to reduce energy consumption.

And, of course, the company is using its AI to build some of the most advanced driverless cars. Google spun out its self-driving car business into its own company, called Waymo, late last year, but it still falls under the broader umbrella of Alphabet companies. The opportunity for Alphabet here is in using AI-powered self-driving technology to earn revenues from self-driving car services, and in selling the technology to other companies to implement in their own vehicles. Waymo is already testing its technology with public riders in Phoenix, as part of a partnership with Fiat Chrysler.

Additionally, Google is using its AI to improve its voice assistant, called Google Assistant. Google Assistant now comes on newer versions of Android phones and in the company's smart home speaker, Google Home. Smart home speakers are expected to become a $13 billion market by 2024.

But Alphabet's biggest opportunity in AI remains in how it's used to sell more ads. Google's ad revenue accounted for 88% of Alphabet's total revenue in 2016, so it's very likely that the company will continue to apply its AI efforts to keep that trend going.

Remember that the artificial intelligence market is just getting started, which means that there's tons of time to reap the benefits, but it could also be a while before the market takes off. Investors looking to Alphabet and NVIDIA for AI gains will likely get them -- but should plan for the benefits to come over the next several years, as opposed to the next few quarters.

Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Teresa Kersten is an employee of LinkedIn and is a member of The Motley Fool's board of directors. LinkedIn is owned by Microsoft. Chris Neiger has no position in any stocks mentioned. The Motley Fool owns shares of and recommends Alphabet (A and C shares), Apple, Facebook, Nvidia, and Tesla. The Motley Fool recommends Intel. The Motley Fool has a disclosure policy.

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2 Top Stocks for Artificial Intelligence Investors -- The Motley Fool - Motley Fool

It is increasingly looking like the future belongs to artificial intelligence.

Two of the hottest stocks in that industry are Nvidia NVDA, +1.04% and Advanced Micro Devices AMD, -2.32% The strength of those stocks is largely attributable to the excitement around the artificial-intelligence capabilities of their processors.

A key to success in hot technology companies is to keep an eye on newly developing competition. Prudent investors tend to sell into strength when new competition emerges. The momo (momentum) crowd is often left holding the bag.

Increased competition may be coming to Nvidia and AMD in the form of a new artificial-intelligence processor thats 10 times more powerful than their current offerings. Lets take a look at this. First, a chart.

Chart

Please click here for the annotated chart. Its a 30-minute chart of Nvidia covering the period during which the smart money has been taking the news of potential new competition into its analysis.

Please note from the chart that the VUD indicator has been consistently orange. The VUD indicator is the most sensitive measure of supply and demand in real time. Orange indicates a higher supply than demand. The VUD indicator staying mostly orange when the price does not move much or goes higher is often an early indicator of the strength of sellers in a stock.

Ask Arora: Nigam Arora answers your questions about investing in stocks, ETFs, bonds, gold and silver, oil and currencies. Have a question? Send it to Nigam Arora.

New competitor is a heavyweight

The new competitor is Fujitsu FJTSY, +4.47% of Japan. Fujitsu was founded in 1935 and employees 159,000 people in more than 100 countries. Fujitsu produces some of the most advanced processors for super computers. Fujitsu also produces processors for SPARC servers. SPARC servers have been popular and are now owned by Oracle ORCL, +0.02% after the company bought Sun Microsystems.

The new processor from Fujitsu will consist of 16 deep-learning processing elements, each of which will contain eight execution units. Fujitsu is targeting 10 times the performance of Nvidia and AMD processors. The new processor will be available in 2018.

Previously, another heavyweight, Intel INTC, +0.17% announced it would introduce competing processors for artificial-intelligence applications.

The software hurdle

As an engineer, I am reasonably confident that competitors are likely to come up with better hardware than Nvidia and AMD. However, the new competitors may have a difficult time catching Nvidia in software and development tools.

Investment implications

The momo crowd is still aggressively buying those stocks, but the smart money is inactive. Please see Professional investors are no longer excited about popular technology stocks and Momentum investors buy stocks even though gold and bonds are warning them buys stocks.

Prudent investors ought to pay attention to actions of the smart money. Yes, there are potential rewards in Nvidia and AMD, but the risks are high. It is fine to trade them for the short term when good setups appear, but caution is warranted if investing for the long term.

Based on my 30 years-plus in the markets, my firm conclusion is that most investors are better off by focusing on risk-adjusted returns. I have repeatedly seen traders who ignore risk making lots of money and then losing it all.

Disclosure: Subscribers to The Arora Report may have positions in the securities mentioned in this article or may take positions at any time. All recommended positions are reviewed daily at The Arora Report.

Nigam Arora is an investor, engineer and nuclear physicist by background, has founded two Inc. 500 fastest-growing companies, is the developer of the adaptive ZYX Global Multi Asset Allocation Model and the ZYX Change Method to profit from change in trading and investing. He is the founder of The Arora Report, which publishes four newsletters. Nigam can be reached at Nigam@TheAroraReport.com.

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Opinion: Nvidia and AMD must brace for competition from a super-powerful artificial-intelligence processor - MarketWatch