OpenAI has announced ‘The Stargate Project,’ a new company set to invest $500 billion into AI infrastructure over the next four years
The data centers will be exclusively used by OpenAI as it expands its generative AI compute portfolio. Of the total investment, $100bn will be deployed ‘immediately.’
SoftBank, OpenAI, Oracle, and Abu Dhabi’s MGX are the equity investors in Stargate, with SoftBank having financial responsibility and OpenAI having operational responsibility. SoftBank’s Masayoshi Son will serve as chairman.
The buildout is currently underway, starting in Texas – likely Oracle’s project in Abilene, Texas, which is itself leased from Crusoe. — Read More
Daily Archives: January 23, 2025
BrowserAI
Deepseek: The Quiet Giant Leading China’s AI Race
Deepseek is a Chinese AI startup whose latest R1 model beat OpenAI’s o1 on multiple reasoning benchmarks. Despite its low profile, Deepseek is the Chinese AI lab to watch.
… Deepseek’s strategy is grounded in their ambition to build AGI. Unlike previous spins on the theme, Deepseek’s mission statement does not mention safety, competition, or stakes for humanity, but only “unraveling the mystery of AGI with curiosity”. Accordingly, the lab has been laser-focused on research into potentially game-changing architectural and algorithmic innovations.
Deepseek has delivered a series of impressive technical breakthroughs. Before R1-Lite-Preview, there had been a longer track record of wins: architectural improvements like multi-head latent attention (MLA) and sparse mixture-of-experts (DeepseekMoE) had reduced inference costs so much as to trigger a price war among Chinese developers. Meanwhile, Deepseek’s coding model trained on these architectures outperformed open weights rivals like July’s GPT4-Turbo.
As a first step to understanding what’s in the water at Deepseek, we’ve translated a rare, in-depth interview with CEO Liang Wenfeng, originally published this past July on a 36Kr sub-brand. — Read More
AI Will Write Complex Laws
Artificial intelligence (AI) is writing law today. This has required no changes in legislative procedure or the rules of legislative bodies—all it takes is one legislator, or legislative assistant, to use generative AI in the process of drafting a bill.
In fact, the use of AI by legislators is only likely to become more prevalent. There are currently projects in the US House, US Senate, and legislatures around the world to trial the use of AI in various ways: searching databases, drafting text, summarizing meetings, performing policy research and analysis, and more. A Brazilian municipality passed the first known AI-written law in 2023.
That’s not surprising; AI is being used more everywhere. What is coming into focus is how policymakers will use AI and, critically, how this use will change the balance of power between the legislative and executive branches of government. Soon, US legislators may turn to AI to help them keep pace with the increasing complexity of their lawmaking—and this will suppress the power and discretion of the executive branch to make policy. — Read More
Deep-learning enabled generalized inverse design of multi-port radio-frequency and sub-terahertz passives and integrated circuits
Millimeter-wave and terahertz integrated circuits and chips are expected to serve as the backbone for future wireless networks and high resolution sensing. However, design of these integrated circuits and chips can be quite complex, requiring years of human expertise, careful tailoring of hand crafted circuit topologies and co-design with parameterized and pre-selected templates of electromagnetic structures. These structures (radiative and non-radiative, single-port and multi-ports) are subsequently optimized through ad-hoc methods and parameter sweeps. Such bottom-up approaches with pre-selected regular topologies also fundamentally limit the design space. Here, we demonstrate a universal inverse design approach for arbitrary-shaped complex multi-port electromagnetic structures with designer radiative and scattering properties, co-designed with active circuits. To allow such universalization, we employ deep learning based models, and demonstrate synthesis with several examples of complex mm-Wave passive structures and end-to-end integrated mm-Wave broadband circuits. The presented inverse design methodology, that produces the designs in minutes, can be transformative in opening up a new, previously inaccessible design space. — Read More
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