Cloud Hosting

For years, EDA companies have claimedartificial intelligence features in their IC design tools. In the past year, however,generative AI has undergone adramatic evolutionwith platforms like ChatGPT, causing some designers to question whether previous EDA features still count as AI by today's standards.

Synopsys aims to keep pace with this accelerating field by unveilinga new extension to its Synopsys.ai EDA suite. This announcement follows the release ofGoogles DeepMind, which uses AI to accelerate its in-house chip designs. Both of these announcements indicate how advanced machine learning algorithms are shaping IC development and how they might be used as a tool for designers in such fields.

Synopsys describes itsnew extension as an AI-driven analytics tool designed to span the entire integrated circuit development process, from initial design to manufacturing and testing. To this end, the Synopsys EDA Data Analytics solution offers several features that set it apart.

First, it provides comprehensive data aggregation capabilities, pulling in data from various stages of IC design, testing, and manufacturing. This gives designersa holistic view of the entire chip development lifecycle. The tool incorporates intelligence-guided debugging and optimization, which not only speeds up design closure but also minimizes project risks. This is particularly crucial in an industry where time to market can be a make-or-break factor.

Another standout feature of the extension is its focus on fabrication yield. This tool is designed to improve fab yield for faster ramp-up and more efficient high-volume manufacturing. Additionally, the tool can uncover silicon data outliers across the semiconductor supply chain, thereby improving chip quality, yield, and throughput.

Synopsys says the new tools can alsouncover new opportunities in power, performance, and area (PPA). By leveraging advanced AI algorithms, the tool can analyze magnitudes of heterogeneous, multi-domain data to accelerate root-cause analysis.

The news from Synopsys comes on the heels of a similar announcement from Google's parent company, Alphabet.

Recently, the group announced that it would be leveraging Google's DeepMind for AI-assisted chip design for use in its data centers. DeepMind usesa concept known as circuit neural networks to treata circuit as if it were a neural network, turning edges into wires and nodes into logic gates.

Then, using classical AI techniques like simulated annealing, DeepMind searches for the most efficient configurations, looking many steps into the future to improve circuit design. Utilizing advanced AI models like AlphaZero and MuZero, which are based on reinforcement learning, DeepMind has achieved "superhuman performance" in various circuit-design tasks.

While both Synopsys and Google's DeepMind are leveraging artificial intelligence to revolutionize chip design, their approaches and focus areas are distinct.

Synopsys' newly announced solution is part of its broader Synopsys.ai EDA suite, which aims to provide designers with an end-to-end, comprehensive toolset for the entire IC chip development lifecycle. These tools aggregate and analyze data across multiple domains to enable intelligent decision-making, speed up design closure, and improve fabrication yield.

DeepMind, on the other hand, takes a more specializedapproach. It employs advanced AI models to tackle specific optimization problems within chip design. While highly effective, this approach is more narrow in scope, focusing on individual aspects of the chip design process rather than offering a comprehensive, full-stack solution. Unlike Synopsys tool, DeepMinds AI is only for the internal optimization of Googles hardware.

Featured image (modified) used courtesy of Synopsys.

Read more here:
From Synopsys to Google, New EDA Tools Apply Advanced AI to IC ... - All About Circuits

Science and nature books

The co-founder of DeepMind issues a terrifying warning about AI and synthetic biology but how seriously should we take it?

Scott Shapiro

On 22 February1946, George Kennan, an American diplomat stationed in Moscow, dictated a 5,000-word cable to Washington. In this famous telegram, Kennan warned that the Soviet Unions commitment to communism meant that it was inherently expansionist, and urged the US government to resist any attempts by the Soviets to increase their influence. This strategy quickly became known as containment and defined American foreign policy for the next 40 years.

The Coming Wave is Suleymans book-length warning about technological expansionism: in close to 300 pages, he sets out to persuade readers that artificial intelligence (AI) and synthetic biology (SB) threaten our very existence and we only have a narrow window within which to contain them before its too late. Unlike communism during the cold war, however, AI and SB are not being forced on us. We willingly adopt them because they not only promise unprecedented wealth, but solutions to our most intractable problems climate change, cancer, possibly even mortality. Suleyman sees the appeal, of course, claiming that these technologies will usher in a new dawn for humanity.

An entrepreneur and AI researcher who co-founded DeepMind in 2010, before it was acquired by Google in 2014, Suleyman is at his most compelling when illustrating the promises and perils of this new world. In breezy and sometimes breathless prose, he describes how human beings have finally managed to exert power over intelligence and life itself.

Take the AI revolution. Language models such as ChatGPT are just the beginning. Soon, Suleyman predicts, AI will discover miracle drugs, diagnose rare diseases, run warehouses, optimise traffic, and design sustainable cities. We will be able to tell a computer program to make a $1 million on Amazon in a few months and it will carry out our instructions.

The problem is that the same technologies that allow us to cure a disease could be used to cause one which brings us to the truly terrifying parts of the book. Suleyman notes that the price of genetic sequencing has plummeted, while the ability to edit DNA with technologies such as Crispr has vastly improved. Soon, anyone will be able to set up a genetics lab in their garage. The temptation to manipulate the human genome, he predicts, will be immense.

Human mutants, however, are not the only horrors awaiting us. Suleyman envisions AI and SB joining forces to enable malicious actors to concoct novel pathogens. With a 4% transmissibility rate (lower than chickenpox) and 50% case fatality rate (about the same as Ebola), an AI-designed and SB-engineered virus could cause more than a billion deaths in a matter of months.

Despite these risks, Suleyman doubts any nation will make the effort to contain these technologies. States are too dependent on their economic benefits. This is the basic dilemma: we cannot afford not to build the very technology that might cause our extinction. Sound familiar?

The Coming Wave is not about the existential threat posed by superintelligent AIs. Suleyman thinks that merely smart AIs will wreak havoc precisely because they will vastly increase human agency in a very short period. Whether via AI-generated cyber-attacks, homebrewed pathogens, the loss of jobs due to technological change, or misinformation aggravating political instability, our institutions are not ready for this tsunami of tech.

He repeatedly tells us that the wave is coming, the coming wave is coming, even the coming wave really is coming. I suppose living through the past 15 years of AI research, and becoming a multimillionaire in the process, would turn anyone into a believer. But if the past is anything to go by, AI is also known for its winters, when initial promise stalled and funding dried up for long periods. Suleyman disregards the real possibility that this will happen again, thereby giving us more time to adapt to and even stem the tide of social change.

But even if progress continues its frenetic pace, it is unlikely that societies will tolerate the ethical abuses Suleyman fears most. When a Chinese scientist revealed in 2018 that he had edited the genes of twin girls, he was sentenced to three years in prison, universally condemned, and there have been no similar reports since. The EU is set to prohibit certain forms of AI such as facial recognition in public spaces in its forthcoming AI Act. Normal legal and cultural pushback will probably slow the proliferation of the most disruptive and disturbing practices.

Despite claiming that the containment problem is the defining challenge of our era, Suleyman does not support a tech moratorium (he did just start a new AI company). Instead he sets out a series of proposals at the end of the book. They are unfortunately not reassuring.

For example, Suleyman suggests that AI companies spend 20% of R&D funds on safety research, but does not say why companies would divert capital away from rushing their new products to market. He advocates banning AI in political ads, but doing so would violate the first amendment to the US constitution. He proposes an international anti-proliferation treaty, but does not give us any indication of how it might be enforced. At one point, Suleyman hints that the US may need to coerce other countries to comply. Some measure of anti-proliferation is necessary. And, yes, lets not shy away from the facts; that means real censorship, possibly beyond national borders. I dont know exactly what he means here, but I dont like the way it sounds.

Suleyman pushes these costly proposals despite conceding that his catastrophic scenarios are tail risks. Yes, the probability of doomsday is low, but the consequences would be so catastrophic that we must treat the possibility as a clear and present danger. One very large elephant in the room is climate change. Unlike the AI apocalypse that may happen in the future, a climate emergency is happening right now. This July was the hottest on record. Containing carbon, not AI, is the defining challenge of our era. Yet here, Suleyman is strikingly and conveniently optimistic. He believes that AI will solve the climate emergency. That is a happy thought but if AI will solve the climate problem, why cant it solve the containment problem too?

If the books predictions about AI are accurate, we can safely ignore its proposals. Wait a few years and we can just ask ChatGPT-5, -6, or -7 how to handle the coming wave.

Scott Shapiro is professor of law and philosophy at Yale and author of Fancy Bear Goes Phishing (Allen Lane). The Coming Wave by Mustafa Suleyman and Michael Bhaskar is published by Bodley Head (25). To support the Guardian and Observer order your copy at guardianbookshop.com. Delivery charges may apply.

{{topLeft}}

{{bottomLeft}}

{{topRight}}

{{bottomRight}}

{{.}}

Go here to read the rest:
The Coming Wave by Mustafa Suleyman review a tech tsunami - The Guardian

While the Federal Election Commission hasnt set rules on using AI in political campaign ads, in August it voted to seek public comments on whether to update its misinformation policy to include deceptive AI ads.

The Google policy change also comes as Congress is working on comprehensive legislation to set guardrails on AI, and is meeting with leaders next week in the generative AI space, including Google CEO Sundar Pichai, which owns AI subsidiary DeepMind.

The specifics: Googles latest rule update which also applies to YouTube video ads requires all verified advertisers to prominently disclose whether their ads contain synthetic content that inauthentically depicts real or realistic-looking people or events. The company mandates the disclosure be clear and conspicuous on the video, image or audio content. Such disclosure language could be this video content was synthetically generated, or this audio was computer generated, the company said.

A disclosure wouldnt be required if AI tools were used in editing techniques, like resizing or cropping, or in background edits that dont create realistic interpretations of actual events.

Political ads that dont have disclosures will be blocked from running or later removed if they evaded initial detection, said a Google spokesperson, but advertisers can appeal, or resubmit their ads with disclosures.

Elections worldwide: Googles policy updates its existing election ads rules in regions outside the U.S. as well, including Europe, India and Brazil which all have elections in 2024 as well. It will also apply to advertisements using deepfakes, which are videos or images that have been synthetically created to mislead, that are banned under the companys existing misrepresentation policy.

Facebook currently doesnt require the disclosure of synthetic or AI-generated content in its ads policies. It does have a policy banning manipulated media in videos that are not in advertisements, and bans the use of deepfakes.

Link:
Google to require disclosure of AI use in political ads - POLITICO

IN OCTOBER 2021, Phil Howard, an internet researcher at the University of Oxford, was alerted to a preposterous story on social media. It alleged that the covid-19 pandemic was started by a shipment of Maine lobsters that arrived in Wuhan, China, days before the first outbreak. He and his colleagues spent months trying to track down the source and didnt get to the bottom of it except that it probably originated in China, possibly through the state-owned TV channel CGTN.

I felt my career had hit a new low, says Howard. What was so ridiculous was the enormous effort that we needed to expose a ridiculous attempt to manipulate public opinion. I realised that I didnt want to do that work myself, so I decided to try and come up with an initiative that would do something about the problem in a systematic way.

Today, Howard is chair of a new organisation called the International Panel on the Information Environment, one of many initiatives pushing back against the pollution of the information ecosystem. Regulators, too, are finally lacing up their own boots after spending years sitting on their hands.

The stakes couldnt be higher, with the recent rise of generative artificial intelligence and its capacity to produce persuasive disinformation on an industrial scale. Many researchers are saying that the next two years are make or break in the information wars, as deep-pocketed bad actors escalate their disinformation campaigns, while the good guys fight back. Which side prevails will determine how the information environment and everything it shapes, from peoples beliefs about vaccines to the outcomes of elections

Read the original here:
Disinformation wars: The fight against fake news in the age of AI - New Scientist

Connor Coley, 29, developed open-source software that uses artificial intelligence to help discover and synthesize new molecules. The suite of tools, called ASKCOS, is used in production by over a dozen pharmaceutical companies, and tens of thousands of chemists, to create new medicines, new materials, and more efficient industrial processes.

One of the largest bottlenecks in developing new molecules has long been identifying interesting candidates to test. This process has played out in more or less the same way for decades: make a small change to a known molecule, and then test the novel creation for its biological, chemical, or physical properties.

Coleys approach includes a form of generative AI for chemistry. A chemist flags which properties are of interest, and AI-driven algorithms suggest new molecules with the greatest potential to have those properties. The system does this by analyzing known molecules and their current properties, and then predicting how small structural changes are likely to result in new behaviors.

As a result, chemists should spend less time testing candidates that never pan out. The types of methods that we work on have led to factors of maybe two, three, maybe 10 [times] reduction in the number of different shots on goal you need to find something that works well, says Coley, who is now an assistant professor of chemical engineering and computer science at MIT.

Once it identifies the candidate molecules, Coleys software comes up with the best way to produce them. Even if chemists imagine or dream up a molecule, he says, figuring out how to synthesize something isnt trivial: We still have to make it.

To that end, the system gives chemists a recipe of steps to follow that are likely to result in the highest yields. Coleys future work includes figuring out how to add laboratory robots to the mix, so that even more automated systems will be able test and refine the proposed recipes by actually following them.

View post:
Pranav Rajpurkar - MIT Technology Review