AI Research
Senator Wiener Expands AI Bill Into Landmark Transparency Measure Based on Recommendations of Governor’s Working Group
SACRAMENTO – Senator Scott Wiener (D-San Francisco) announced amendments to expand Senate Bill (SB) 53 into a first-in-the-nation transparency requirement for the largest AI companies. The new provisions draw on the recommendations of a working group led by some of the world’s leading AI experts and convened by Governor Newsom. Building on the report’s “trust, but verify” approach, the amended bill requires the largest AI companies to publicly disclose their safety and security protocols and report the most critical safety incidents to the California Attorney General. The requirements codify voluntary agreements made by leading AI developers to boost trust and accountability and establish a level playing field for AI development.
SB 53 retains provisions — called “CalCompute” — that advance a bold industrial strategy to boost AI development and democratize access to the most advanced AI models and tools. CalCompute will be a public cloud compute cluster housed at the University of California that provides free and low-cost access to compute for startups and academic researchers. CalCompute builds on Senator Wiener’s recent legislation to boost semiconductor and other advanced manufacturing in California by streamlining permit approvals for advanced manufacturing plants, and his work to protect democratic access to the internet by authoring the nation’s strongest net neutrality law.
SB 53 also retains its protections of whistleblowers at AI labs who disclose significant risks.
Weeks ago, the U.S. Senate voted 99-1 to remove provisions of President Trump’s “Big Beautiful Bill” that would have prevented states from enacting AI regulations. By boosting transparency, SB 53 builds on this vote for accountability.
“As AI continues its remarkable advancement, it’s critical that lawmakers work with our top AI minds to craft policies that support AI’s huge potential benefits while guarding against material risks,” said Senator Wiener. “Building on the Working Group Report’s recommendations, SB 53 strikes the right balance between boosting innovation and establishing guardrails to support trust, fairness, and accountability in the most remarkable new technology in years. The bill continues to be a work in progress, and I look forward to working with all stakeholders in the coming weeks to refine this proposal into the most scientific and fair law it can be.”
As AI advances, risks and benefits grow
Recent advances in AI have delivered breakthrough benefits across several industries, from accelerating drug discovery and medical diagnostics to improving climate modeling and wildfire prediction. AI systems are revolutionizing education, increasing agricultural productivity, and helping solve complex scientific challenges.
However, the world’s most advanced AI companies and researchers acknowledge that as their models become more powerful, they also pose increasing risks of catastrophic damage. The Working Group report states:
Evidence that foundation models contribute to both chemical, biological, radiological, and nuclear (CBRN) weapons risks for novices and loss of control concerns has grown, even since the release of the draft of this report in March 2025. Frontier AI companies’ [including OpenAI and Anthropic] own reporting reveals concerning capability jumps across threat categories.
To address these risks, AI developers like Meta, Google, OpenAI, and Anthropic have entered voluntary commitments to conduct safety testing and establish robust safety and security protocols. Several California-based frontier AI developers have designed industry-leading safety practices including safety evaluations and cybersecurity protections. SB 53 codifies these voluntary commitments to establish a level playing field and ensure greater accountability across the industry.
Background on the report
Governor Newsom convened the Joint California Policy Working Group on AI Frontier Models in September 2024, following his veto of Senator Wiener’s SB 1047, tasking the group to “help California develop workable guardrails for deploying GenAI, focusing on developing an empirical, science-based trajectory analysis of frontier models and their capabilities and attendant risks.”
The Working Group is led by experts including the “godmother of AI” Dr. Fei-Fei Li, Co-Director of the Stanford Institute for Human-Centered Artificial Intelligence; Dr. Mariano-Florentino Cuéllar, President of the Carnegie Endowment for International Peace; and Dr. Jennifer Tour Chayes, Dean of the UC Berkeley College of Computing, Data Science, and Society.
On June 17, the Working Group released their Final Report. While the report does not endorse specific legislation, it promotes a “trust, but verify” framework to establish guardrails that reduce material risks while supporting continued innovation.
SB 53 balances AI risk with benefits
Drawing on recommendations of the Working Group Report, SB 53:
- Establishes transparency into large companies’ safety and security protocols and risk evaluations. Companies will be required to publish their safety and security protocols and risk evaluations in redacted form to protect intellectual property.
- Mandates reporting of critical safety incidents (e.g., model-enabled CBRN threats, major cyber-attacks, or loss of model control) within 15 days to the Attorney General.
- Protects employees and contractors who reveal evidence of critical risk or violations of the act by AI developers.
The bill’s provisions apply only to a small number of well-resourced companies, and only to the most advanced models. The Attorney General has the power to update the thresholds governing which companies are covered under the bill to ensure the requirements keep up with rapid advancements in the field, but must cover only well-resourced companies at the frontier of AI development.
Under SB 53, the Attorney General imposes civil penalties for violations of the act. SB 53 does not impose any new liability for harms caused by AI systems.
In addition, SB 53 creates CalCompute, a research cluster to support startups and researchers developing large-scale AI. The bill helps California secure its global leadership as states like New York establish their own AI research clusters.
SB 53 is sponsored by the Encode AI, Economic Security Action California, and the Secure AI Project.
SB 53 is supported by a broad coalition of researchers, industry leaders, and civil society advocates:
“California has long been the birthplace of major tech innovations. SB 53 will help keep it that way by ensuring AI developers responsibly build frontier AI models,” said Sneha Revanur, president and founder of Encode AI, a co-sponsor of the bill. “This bill reflects a common-sense consensus on AI development, promoting transparency around companies’ safety and security practices.”
“At Elicit, we build AI systems that help researchers make evidence-based decisions by analyzing thousands of academic papers,” said Andreas Stuhlmüller, CEO of Elicit. “This work has taught me that transparency is essential for AI systems that people rely on for critical decisions. SB53’s requirements for safety protocols and transparency reports are exactly what we need as AI becomes more powerful and widespread. As someone who’s spent years thinking about how AI can augment human reasoning, I believe this legislation will accelerate responsible innovation by creating clear standards that make future technology more trustworthy.”
“I have devoted my life to advancing the field of AI, but in recent years it has become clear that the risks it poses could threaten us all,” said Geoffrey Hinton, University of Toronto Professor Emeritus, Turing Award winner, Nobel laureate, and a “godfather of AI.” “Greater transparency requirements into how companies are addressing safety concerns from the most powerful technology of our time is an important step towards addressing those risks.”
“SB 53 is a smart, targeted step forward on AI safety, security, and transparency,” said Bruce Reed, Head of AI at Common Sense Media. “We thank Senator Wiener for reinforcing California’s strong commitment to innovation and accountability.”
“AI can bring tremendous benefits, but only if we steer it wisely. Recent evidence shows that frontier AI systems can resort to deceptive behavior like blackmail and cheating to avoid being shut down or fulfill other objectives,” said Yoshua Bengio, Full Professor at Université de Montréal, Co-President and Scientific Director of LawZero, Turing Award winner and a “godfather of AI.” “These risks must be taken with the utmost seriousness alongside other existing and emerging threats. By advancing SB 53, California is uniquely positioned to continue supporting cutting-edge AI while proactively taking a step towards addressing these severe and potentially irreversible harms.”
“Including safety and transparency protections recommended by Gov. Newsom’s AI commission in SB 53 is an opportunity for California to be on the right side of history and advance commonsense AI regulations while our national leaders dither,” said Teri Olle, Director of Economic Security California Action, a co-sponsor of the bill. “In addition to making sure AI is safe, the bill would create a public option for cloud computing – the critical infrastructure necessary to fuel innovation and research. CalCompute would democratize access to this powerful resource that is currently enjoyed by a tiny handful of wealthy tech companies, and ensure that AI benefits the public. With inaction from the federal government – and on the heels of the defeat of the proposed 10-year moratorium on AI regulations – California should act now and get this done.”
“The California Report on Frontier AI Policy underscored the growing consensus for the importance of transparency into the safety practices of the largest AI developers,” said Thomas Woodside, Co-Founder and Senior Policy Advisor, Secure AI Project, a co-sponsor of the bill. “SB 53 ensures exactly that: visibility into how AI developers are keeping their AI systems secure and Californians safe.”
“Reasonable people can disagree about many aspects of AI policy, but one thing is clear: reporting requirements and whistleblower protections like those in SB 53 are sensible steps to provide transparency, inform the public, and deter egregious practices without interfering with innovation,” said Steve Newman, Technical co-founder of eight technology startups, including Writely – which became Google Docs, and co-creator of Spectre, one of the most influential video games of the 1990s.
###
AI Research
E-research library with AI tools to assist lawyers | Delhi News
New Delhi: In an attempt to integrate legal work in courts with artificial intelligence, Bar Council of Delhi (BCD) has opened a one-of-its-kind e-research library at the Rouse Avenue courts. Inaugurated on July 5 by law minister Kapil Mishra, the library has various software to assist lawyers in their legal work. With initial funding of Rs 20 lakh, BCD functionaries told TOI that they are also planning the expansion of the library to be accessed from anywhere.Named after former BCD chairman BS Sherawat, the library boasts an integrated system, including the legal research platform SCC Online, the legal research online database Manupatra, and an AI platform, Lucio, along with several e-books on law across 15 desktops.Advocate Neeraj, president of Central Delhi Bar Court Association, told TOI, “The vision behind this initiative is to help law practitioners in their research. Lawyers are the officers of the honourable court who assist the judicial officer to reach a verdict in cases. This library will help lawyers in their legal work. Keeping that in mind, considering a request by our association, BCD provided us with funds and resources.”The library, which runs from 9:30 am to 5:30 pm, aims to develop a mechanism with the help of the evolution of technology to allow access from anywhere in the country. “We are thinking along those lines too. It will be good if a lawyer needs some research on some law point and can access the AI tools from anywhere; she will be able to upgrade herself immediately to assist the court and present her case more efficiently,” added Neeraj.Staffed with one technical person and a superintendent, the facility will incur around Rs 1 lakh per month to remain functional.With pendency in Delhi district courts now running over 15.3 lakh cases, AI tools can help law practitioners as well as the courts. Advocate Vikas Tripathi, vice-president of Central Delhi Court Bar Association, said, “Imagine AI tools which can give you relevant references, cite related judgments, and even prepare a case if provided with proper inputs. The AI tools have immense potential.”In July 2024, ‘Adalat AI’ was inaugurated in Delhi’s district courts. This AI-driven speech recognition software is designed to assist court stenographers in transcribing witness examinations and orders dictated by judges to applications designed to streamline workflow. This tool automates many processes. A judicial officer has to log in, press a few buttons, and speak out their observations, which are automatically transcribed, including the legal language. The order is automatically prepared.The then Delhi High Court Chief Justice, now SC Judge Manmohan, said, “The biggest problem I see judges facing is that there is a large demand for stenographers, but there’s not a large pool available. I think this app will solve that problem to a large extent. It will ensure that a large pool of stenographers will become available for other purposes.” At present, the application is being used in at least eight states, including Kerala, Karnataka, Andhra Pradesh, Delhi, Bihar, Odisha, Haryana and Punjab.
AI Research
Enterprises will strengthen networks to take on AI, survey finds
- Private data centers: 29.5%
- Traditional public cloud: 35.4%
- GPU as a service specialists: 18.5%
- Edge compute: 16.6%
“There is little variation from training to inference, but the general pattern is workloads are concentrated a bit in traditional public cloud and then hyperscalers have significant presence in private data centers,” McGillicuddy explained. “There is emerging interest around deploying AI workloads at the corporate edge and edge compute environments as well, which allows them to have workloads residing closer to edge data in the enterprise, which helps them combat latency issues and things like that. The big key takeaway here is that the typical enterprise is going to need to make sure that its data center network is ready to support AI workloads.”
AI networking challenges
The popularity of AI doesn’t remove some of the business and technical concerns that the technology brings to enterprise leaders.
According to the EMA survey, business concerns include security risk (39%), cost/budget (33%), rapid technology evolution (33%), and networking team skills gaps (29%). Respondents also indicated several concerns around both data center networking issues and WAN issues. Concerns related to data center networking included:
- Integration between AI network and legacy networks: 43%
- Bandwidth demand: 41%
- Coordinating traffic flows of synchronized AI workloads: 38%
- Latency: 36%
WAN issues respondents shared included:
- Complexity of workload distribution across sites: 42%
- Latency between workloads and data at WAN edge: 39%
- Complexity of traffic prioritization: 36%
- Network congestion: 33%
“It’s really not cheap to make your network AI ready,” McGillicuddy stated. “You might need to invest in a lot of new switches and you might need to upgrade your WAN or switch vendors. You might need to make some changes to your underlay around what kind of connectivity your AI traffic is going over.”
Enterprise leaders intend to invest in infrastructure to support their AI workloads and strategies. According to EMA, planned infrastructure investments include high-speed Ethernet (800 GbE) for 75% of respondents, hyperconverged infrastructure for 56% of those polled, and SmartNICs/DPUs for 45% of surveyed network professionals.
AI Research
Amazon Web Services builds heat exchanger to cool Nvidia GPUs for AI
The letters AI, which stands for “artificial intelligence,” stand at the Amazon Web Services booth at the Hannover Messe industrial trade fair in Hannover, Germany, on March 31, 2025.
Julian Stratenschulte | Picture Alliance | Getty Images
Amazon said Wednesday that its cloud division has developed hardware to cool down next-generation Nvidia graphics processing units that are used for artificial intelligence workloads.
Nvidia’s GPUs, which have powered the generative AI boom, require massive amounts of energy. That means companies using the processors need additional equipment to cool them down.
Amazon considered erecting data centers that could accommodate widespread liquid cooling to make the most of these power-hungry Nvidia GPUs. But that process would have taken too long, and commercially available equipment wouldn’t have worked, Dave Brown, vice president of compute and machine learning services at Amazon Web Services, said in a video posted to YouTube.
“They would take up too much data center floor space or increase water usage substantially,” Brown said. “And while some of these solutions could work for lower volumes at other providers, they simply wouldn’t be enough liquid-cooling capacity to support our scale.”
Rather, Amazon engineers conceived of the In-Row Heat Exchanger, or IRHX, that can be plugged into existing and new data centers. More traditional air cooling was sufficient for previous generations of Nvidia chips.
Customers can now access the AWS service as computing instances that go by the name P6e, Brown wrote in a blog post. The new systems accompany Nvidia’s design for dense computing power. Nvidia’s GB200 NVL72 packs a single rack with 72 Nvidia Blackwell GPUs that are wired together to train and run large AI models.
Computing clusters based on Nvidia’s GB200 NVL72 have previously been available through Microsoft or CoreWeave. AWS is the world’s largest supplier of cloud infrastructure.
Amazon has rolled out its own infrastructure hardware in the past. The company has custom chips for general-purpose computing and for AI, and designed its own storage servers and networking routers. In running homegrown hardware, Amazon depends less on third-party suppliers, which can benefit the company’s bottom line. In the first quarter, AWS delivered the widest operating margin since at least 2014, and the unit is responsible for most of Amazon’s net income.
Microsoft, the second largest cloud provider, has followed Amazon’s lead and made strides in chip development. In 2023, the company designed its own systems called Sidekicks to cool the Maia AI chips it developed.
WATCH: AWS announces latest CPU chip, will deliver record networking speed
-
Funding & Business1 week ago
Kayak and Expedia race to build AI travel agents that turn social posts into itineraries
-
Jobs & Careers1 week ago
Mumbai-based Perplexity Alternative Has 60k+ Users Without Funding
-
Mergers & Acquisitions1 week ago
Donald Trump suggests US government review subsidies to Elon Musk’s companies
-
Funding & Business1 week ago
Rethinking Venture Capital’s Talent Pipeline
-
Jobs & Careers1 week ago
Why Agentic AI Isn’t Pure Hype (And What Skeptics Aren’t Seeing Yet)
-
Education2 days ago
9 AI Ethics Scenarios (and What School Librarians Would Do)
-
Education3 days ago
Teachers see online learning as critical for workforce readiness in 2025
-
Education3 days ago
Nursery teachers to get £4,500 to work in disadvantaged areas
-
Education5 days ago
How ChatGPT is breaking higher education, explained
-
Jobs & Careers1 week ago
Astrophel Aerospace Raises ₹6.84 Crore to Build Reusable Launch Vehicle