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State of AI 2020 – Article by Pavel Ilin

State of AI 2020 – Article by Pavel Ilin

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Pavel Ilin


This summary is prepared based on the State of AI Report 2020, which was crafted by Nathan Benaich and Ian Hogarth.

The AI industry is very diverse in its application, and it’s going through a transformation from the magical-wand stage to the plateau of adequate development. Let’s take a look at what is happening in the AI industry.

Research

We haven’t come up with new super-smart algorithms. Progress in model performance keeps being driven by big computational budgets and huge data sets. Training of the GPT-3 language model, with its 175 billion parameters, cost approximately $10 million. At the same time larger models require less data to achieve the same level of performance. With a deep-learning approach we are getting close to the point when the cost of training will grow outrageous with incrementally smaller improvements of the model.

An important fact is that the code base of most artificial intelligence systems remains closed. Only 15% of papers publish their code. This raises a lot of concerns about reproducibility and AI safety. AI explainability remains a critical issue for AI safety research; there are promising avenues of exploration such as Asymmetric Shapley Values, but so far it’s unknown how AI systems make decisions. 

Natural language processing (NLP) models successfully simulate common scenes and linguistics, but they fail dramatically with understanding problems and context and forming knowledge. 

Talent

Talented people with skills in math and computer science are the drivers of the progress in the AI field. More and more US professors are being recruited by tech companies. This affects the quality of education that US universities can provide. We already can see a decline in the level of entrepreneurship among recent graduates. At the same time Universities are creating AI-related degree programs.

The US keeps its position as the main attractor of talented individuals. For example China contributes to the talent pool of AI developers, but after publication of their first results, talented people are most likely to move to the US. 90% of international PhD graduates stay and work in US universities and corporations. Demand for AI talent remains much higher than supply, even despite COVID-19’s impact on market growth.  

Industry

AI keeps progressing not only on a theoretical and research level. Many real world applications are already in use, and they are affecting the industries in various ways.

New drugs are being designed by AI, and they are already in clinical trials. For example AI-designed drugs for OCD treatment are out for testing in Japan. AI drug-discovery startups keep raising funds. Also big pharma is teaming up with startups around preserving privacy during drug discovery. For example OpenMined uses federated learning to preserve privacy with medical data. Viz.ai presented the first product which was approved by the Centers for Medicare and Medicaid Services in the US. Their product analyzes tomography scans and alerts specialists who can treat patients before they receive damage that leads to the long-term disability. 

Progress in self-driving cars stays limited. Only 3 companies in California have permission to conduct testing of self-driving cars without a safety driver. Self-driving mileage remains microscopic compared to human drivers (2,874,950 miles for self-driving cars versus 390,313,739,000 miles for humans). The research and development process for self-driving cars remains very expensive. The major companies in this field raised around $7 billion since July 2019. Tesla chose to approach gradually adding self-driving features to its cars, but human drivers still remain in the loop. Recent approaches such as supervised learning do not perform well enough. To make dramatic breakthroughs, new approaches are required.

Computer vision unlocks faster accident and disaster recovery intervention. It also reduces the amount of human hours spent using a microscope, which could lead to acceleration of development processes and reduction of product costs.

AI drives sales and at the same time reduces costs in supply chains and manufacturing. Robotic process automation and computer vision are the most commonly deployed techniques in the enterprise. Speech, natural language generation, and physical robots are the least common. Recently IBM partnered with health insurance company Humana. IBM implemented natural language understanding (NLU) software which is already live and handles calls. It not only redirects calls to the different queues; it’s able to answer basic questions, such as “How much will the copay be to visit a specific specialist?” without human intervention.

Modern AI, in order to perform well, requires a lot of computing resources. Specialized AI hardware keeps progressing, and companies are now presenting second generations of their products. Graphcore M2000 offers faster training time to drop the cost of state-of-the-art models. Google’s new TPU v4 delivers up to a 3.7x training speedup over their TPU v3. NVIDIA will not rest either; it has achieved up to 2.5x training speedups with the new A100 GPU vs V100. Increasing interest towards machine learning devOps is a signal that the industry shifting its focus from how to build models to how to run them.

Despite the COVID-19 pandemic, investments keep coming into the industry. Private funding rounds of greater than $15 million for the AI-first companies remain strong.

Politics

Usage of AI for facial recognition tasks is extremely common around the world. Around half of the world allows facial recognition. This has become a recognizable political and ethical problem, especially when use of this technology leads to the wrong arrests. There were two highly publicized cases of wrong arrest in the US (which is probably just a tip of the iceberg). In May 2019, Detroit police arrested Michael Oliver who was wrongly accused of a felony for supposedly reaching into a teacher’s vehicle, grabbing a cellphone and throwing it, cracking the screen, and breaking the case. In January 2020, Detroit police arrested Robert Williams as a shoplifter who allegedly stole five watches from Midtown’s trendy Shinola store in October 2018. In both cases charges were dismissed but harm was done. 

Industry took a more thoughtful approach as a reaction to the AI mistakes. Microsoft deleted its database of 10 million faces, Amazon announced a one-year pause on letting the police use its facial recognition tool Rekognition. IBM announced it would sunset its general purpose facial recognition products. Washington State in the US introduced requirements to acquire warrants to run facial recognition scans. The ImageNet, a popular image database, is making an effort toward reduction of the biases in its image collections.

As Deep Fake technology produces more and more realistic media, it becomes illegal to use in certain states in the US. California passed a law, AB 730, aimed at deep fakes, which criminalizes distributing audio or video that gives a false, damaging impression of a politician’s words or action. Many other US state bills have been passed, addressing different risks. For example Virginia law amends current criminal law on revenge porn to include computer-generated pornography.

The US government keeps pursuing implementation of the military AI systems. DARPA organised a virtual dogfighting tournament where various AI systems would compete with each other and a human fighter pilot from the US military.

AI nationalism is on the rise. Countries tend to pursue protectionist policies to scrutinize acquisitions of AI companies by the players from other countries.

Every year AI plays a more and more noticeable part in our lives. It becomes cheaper, and you learn how to do new things. But we have to remember that at the moment AI is still a tool. And there are some philosophical and methodological difficulties which we have to overcome before it will be possible to deliberate about the potential sentience of the AI. It’s very important for the policy makers to make informed decisions based on how technology actually works and not on magical understanding formed based on popular sci-fi.

Pavel Ilin is Secretary of the United States Transhumanist Party. 

 

Andrés Grases Interviews U.S. Transhumanist Party Chairman Gennady Stolyarov II on Transhumanism and the Transition to the Next Technological Era

Andrés Grases Interviews U.S. Transhumanist Party Chairman Gennady Stolyarov II on Transhumanism and the Transition to the Next Technological Era

logo_bgGennady Stolyarov II
Andrés Grases


Andrés Grases, the publisher of the Transhuman Plus website (http://transhumanplus.com/) interviews U.S. Transhumanist Party Chairman Gennady Stolyarov II at RAAD Fest 2018 in San Diego, CA, on September 23, 2018. During the course of this conversation, both the contemporary state of transhumanist politics and future directions are covered – along with the challenges to reforming the educational system, the need to create open access to academic works, the manner in which the transition toward the next era of technologies will occur, the meaning of transhumanism and its applications in the proximate future – including promising advances that we can expect to see during the next several years.

Watch the video here.

Become a member of the U.S. Transhumanist Party for free, no matter where you reside. Apply online here in less than a minute.

Third Enlightenment Salon – Gennady Stolyarov II, Bill Andrews, Bobby Ridge, and Mihoko Sekido Discuss Science-Based Advocacy of Transhumanism and Healthy Living

Third Enlightenment Salon – Gennady Stolyarov II, Bill Andrews, Bobby Ridge, and Mihoko Sekido Discuss Science-Based Advocacy of Transhumanism and Healthy Living

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Gennady Stolyarov II
Bill Andrews
Bobby Ridge
Mihoko Sekido


The Third Enlightenment Salon, hosted by Gennady Stolyarov II on May 27, 2018, featured excellent conversations on the rise in public awareness of transhumanism and life extension and what can be done to further increase support for life-extending medical research. Dr. Bill Andrews, Bobby Ridge (a.k.a. Robert Ridge), and Mihoko Sekido shared insights on medical science, promotion of health, and methods of communicating the forthcoming convergence of advances in a wide array of technological fields. Importantly, we addressed how anyone can get involved in the transhumanist movement and improve public acceptance of the emerging technological future.

The following were some interesting areas of discussion:

– The new Telomere Coin, which will help fund Dr. Andrews’s research efforts – http://defytime.group/
– Bobby Ridge’s forthcoming new video channel – Science-Based Species
– Aspects of online videos that help increase their reach
– Factors that contribute to longer lifespans among Okinawans
– Motivators for leading a healthier lifestyle and its relation to the recognition of the possibility of indefinite life extension in our lifetimes
– Some potential health effects of metformin and the importance of the ongoing TAME clinical trials
– What anyone can do to promote life extension and other emerging technological fields – including joining the U.S. Transhumanist Party for free on this page.

This video also contains some excerpts from the remaining conversations at the Third Enlightenment Salon, including discussions of science-based medicine, promotion of transhumanism, autonomous vehicles, and responses to the prospect of longevity escape velocity.

Along with the recorded segment, there was much discussion about future directions of transhumanist initiatives, reasonably healthy food in a refined atmosphere, and previews of excellent video compilations that will become publicly available later this year. Mr. Stolyarov looks forward to hosting more Enlightenment Salons to bring together individuals in various fields of expertise and enable them to synthesize their insights into ways of comprehensively improving the human condition.

The U.S. Transhumanist Party Responds to Jeremy Rifkin’s Plan for a Third Industrial Revolution

The U.S. Transhumanist Party Responds to Jeremy Rifkin’s Plan for a Third Industrial Revolution

Gennady Stolyarov II


Photograph of Jeremy Rifkin by Stephan Röhl

Editor’s Note: Below is a response to Jeremy Rifkin’s plan for a Third Industrial Revolution: A Radical New Sharing Economy by Gennady Stolyarov II, Chairman of the U.S. Transhumanist Party. The original post of this documentary can be found here.

    ~ Dinorah Delfin, Director of Admissions and Public Relations, U.S. Transhumanist Party, March 10, 2018

When it comes to Jeremy Rifkin’s thoughts on the future, and what humankind will and will not be able to accomplish, Arthur C. Clarke’s famous First Law encapsulates my reaction: “When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.”

I think that Rifkin has many ideas that would be aligned with transhumanism, although his general worldview is not transhumanist in itself. I wholly support the concepts of the sharing economy, the goal of production at zero marginal cost, and the smart infrastructure that he describes would support the Third Industrial Revolution. A redesign of our infrastructure – especially in such a way that would facilitate modular upgrades at a local and even individual level – is essential for overcoming some of the current bottlenecks to technological progress and rising standards of living. I also think that Rifkin is correct that, in the short term, building this new infrastructure will require humans and will mean jobs for those humans. This is probably a good thing, although it is dependent on whether the systems for financing the new projects and appropriately recruiting and treating the workers (e.g., giving them high-quality jobs with good pay, safety precautions, and ample assistance from machines and narrow AIs where possible) can come together in time.

Where I think Rifkin falls short of the transhumanist vision is in his rejection of the goal of a society where basic human problems – including mortality and many of the other key causes of suffering – can be eliminated or at least greatly reduced. He characterizes this as “utopian” thinking, but at every stage of the way, the approach toward these goals would not be utopia, but rather steady improvement. It would be a shame to reject the goals especially as the technologies for making them possible are becoming available. As I have often stated, it is not a matter of if we will have indefinite life extension, but when – and this matters a lot from the standpoint of how many people alive today could be saved.

Where I also differ from Rifkin is that, instead of his focus on the negative (“humans are destroying the Earth”), I and the Transhumanist Party prefer to focus on the positive potentials (humans can improve both our own lives and the Earth through emerging technologies). Many of the solutions may look quite similar – e.g., smart infrastructure, greater energy-efficiency, and renewable energy sources that would move humankind away from fossil fuels (although, unlike Rifkin, I also strongly support the next generation of nuclear reactors, which would use thorium, would be meltdown-proof, and would not be subject to the need for cooling via massive amounts of water that Rifkin criticizes). I think that the way forward is through technological advancement; Rifkin is halfway there – certainly much better than the Neo-Luddite thinkers who have often dominated the environmental movement. But his goals are not in conflict with life extension, massive economic growth, and super-abundance of material prosperity for everyone. In fact, humans need to move along all of these avenues simultaneously and in parallel, as their achievements will reinforce one another and enable progress to occur more readily.

Article III, Section IX of our Platform – http://transhumanist-party.org/constitution/#Article3 – actually summarizes this sentiment quite nicely: “The United States Transhumanist Party supports all emerging technologies that have the potential to improve the human condition – including but not limited to autonomous vehicles, electric vehicles, economical solar power, safe nuclear power, hydroelectricity, geothermal power, applications for the sharing of durable goods, artificial intelligence, biotechnology, nanotechnology, robotics, rapid transit, 3D printing, vertical farming, electronic devices to detect and respond to trauma, and beneficial genetic modification of plants, animals, and human beings.”

Again, Clarke’s First Law comes to mind. To the extent that Rifkin sees potential in any of the above technologies and others, he is correct. To the extent that he does not see it or considers those technologies to be detrimental, he is mistaken.