Google and RWE Back German Nuclear Startup Proxima Fusion at €2.4 Billion Valuation German startup Proxima Fusion has raised €411 million ($469 million) from a range of investors, including national energy firm RWE AG and Alphabet Inc.’s Google, to develop a nuclear fusion plant it hopes will be operational in the 2030s. XTX Ventures, the investment arm from Alex Gerko’s algorithmic trading firm XTX Markets Ltd, led the financing round with London-based firm East X Ventures. The deal gives the three year-old energy firm a valuation of €2.4 billion, Proxima Fusion said on Tuesday. (Bloomberg)

A PhD student built a working nuclear fusion reactor in his garage, let an AI run it, and 400 thousand dollars later he works for Elon Musk. he posted it once. that single post ended with a grant in his account and a job offer from the most powerful man on earth. not a simulation. not a school project. an actual device that fuses atoms, sitting where his car used to be. fusion is the thing governments have been chasing for 70 years with billion dollar labs. the hard part was never the reactor itself. it was the control. the plasma inside has to be held at conditions hotter than the core of the sun, and it shifts and collapses in milliseconds. no human can react fast enough to keep it stable. so he stopped trying to do it himself. he handed the control loop to an AI. the model reads the sensor data hundreds of times a second, predicts how the plasma is about to move, and adjusts the magnetic fields before it ever drifts out of line. it does not wait for the plasma to misbehave. it sees it coming and corrects it before it happens. the same reaction-before-the-event speed no person could ever match. this is the exact kind of build people are tearing apart inside @NeuroClubAi. not to make reactors, but because the workflow is identical for anything hard. let the AI run the loop, predict the problem, fix it before it breaks. same playbook whether it is plasma or a business. then the post went out. within days Elon's fusion team reached out. they did not ask him to interview for an entry role. they handed him a 400 thousand dollar grant and pulled him onto the team building this at scale. one garage build turned a PhD student into an operator for the most ambitious man alive. here is the part that should stop you. he was one guy with a PhD, a garage, and an AI model doing the job that entire teams of physicists used to fail at. the AI was not assisting him. it was the operator. he built the hardware. the machine ran it. and that was enough to get noticed at the very top. most people think AI writes emails and makes pictures. meanwhile someone pointed it at one of the hardest physics problems on earth, held the plasma steady, and got paid by Elon Musk for it. the gap is not between humans and AI anymore. it is between the people who realize what this thing can already do and the people still using it to summarize their inbox.

AI needs a lot of power. Could nuclear fusion be part of the answer? 🎙️ Jordan Isvy and Patrick Coffey discuss the reasons why the race to commercialise fusion as an energy source is gaining momentum.

⚡️Energy Brief⚡️ The UK Atomic Energy Authority launched a comprehensive strategy for nuclear fusion development and deployment. The strategy includes completing the detailed design phase of the UK's STEP fusion prototype power plant, a government-supported initiative to demonstrate fusion technology for commercial application. The strategy emphasizes expanding the UK fusion supply chain and increasing participation from UK fusion companies. This approach aims to build domestic industrial capacity and economic value creation around fusion energy commercialization. The comprehensive fusion strategy reflects governmental commitment to positioning the UK as a center for fusion innovation and manufacturing. By advancing both demonstration projects and supply chain development, the UKAEA's approach addresses both technical validation and economic development objectives in the emerging fusion energy sector. @UKAEAuthority Source: World Nuclear News

Elon really put into perspective just how insanely massive the Sun is compared to Earth The Sun contains ~99.86% of all the mass in the entire Solar System Earth is basically a rounding error We live on this tiny rock next to an object so massive that almost everything else in the Solar System barely registers And that giant ball of nuclear fusion is dumping an unimaginable amount of energy into space every second

JUST IN: SAM ALTMAN'S BUSINESS DEALINGS ARE UNDER FEDERAL SCRUTINY AHEAD OF OPENAI'S IPO The House Oversight Committee launched a probe. Six GOP state AGs are asking the SEC to review. The specific deals in the spotlight: - Helion: Altman is a personal investor in the nuclear fusion firm. OpenAI was reportedly asked to back Helion, per WSJ. Altman recused himself from recent discussions. - Stoke Space: Altman invested through his family office. Last summer he reportedly asked the rocket-maker about partnering with OpenAI to build data centers in space. The scrutiny: - House Oversight Committee Chairman James Comer sent a letter Friday requesting a briefing on potential conflicts of interest. - Six state AGs (Florida, Montana, Nebraska, Iowa, West Virginia, Louisiana) wrote to SEC Chairman Paul Atkins, asking for review ahead of the IPO. - The AGs flagged that Altman "has no direct equity in OpenAI," so "his personal financial interests have only limited alignment with OpenAI's financial performance." The IPO backdrop: - OpenAI is valued at roughly $850 billion in the private market. - The IPO is expected to be one of the largest ever. - The company is expected to quickly enter major indexes and ETFs post-listing. OpenAI board chairman Bret Taylor testified Monday that Altman had been "forthright" and "proactive and transparent" about his outside involvements.

Managing Chaos in Atoms and Markets: Michael Egorov on Physics, Liquidations, and Financial Engineering Shoal Signal Ep. 19 with @newmichwill, founder of @CurveFinance and @yieldbasis, hosted by @zaddycoin We cover how cooling atoms to 100 nanokelvins taught him to trust an invariant instead of a price, why he took impermanent loss on a trade on purpose, the half year he sat in liquidation on purpose to test Curve, and why nuclear fusion gets solved sooner than the field expects. 0:00 Photons look like giant cucumbers 0:58 What coherence time actually is 4:46 Bose-Einstein condensate and laser cooling 8:47 A qubit that held for seconds 11:36 From ideal atoms to ideal markets 13:50 The invariant is the only signal 15:08 Control systems in the lab and DeFi 16:42 Quantum finance and prices tunneling 18:49 A toy universe made of vortices 21:18 Why there is no antimatter around us 23:57 Crypto as the revolution in money 25:29 Cycles from Mt. Gox to meme coins 30:40 Where retail's next opportunity sits 33:36 The Web3 promise that never landed 35:28 Why crypto fits agents better than humans 39:09 Working only on impossible problems 40:00 Solving impermanent loss with Yield Basis 40:48 Reversible liquidation in Curve 42:26 Half a year in liquidation on purpose 45:42 Where the risk actually sits 49:45 Paying authors when AI trains on books 53:28 Energy as the next breakthrough 57:17 Two roads to fusion 1:03:33 Thorium and the economics of nuclear 1:08:13 Where the alpha is 1:10:21 Turning mercury into gold in San Francisco

Honored to be named one of the 100 most influential people in AI by @TIME right on the heels of the public launch of our company Accelerated Understanding @accelerated_u Bringing the power of AI+Science together has been the focus of my life for the past decade. I believe the greatest impact AI can have on science and engineering is its ability to massively accelerate simulation and understanding of the physical world. We started this journey with the invention of Neural Operators at @Caltech to have a powerful foundation for AI modeling physical phenomena at multiple scales. Together with my team at @nvidia and support from @JensenHuang himself we built FourCastNet, the first high-resolution AI-weather model that is tens of thousands of times faster than existing systems. Following up on this success we have applied Neural Operators to accelerating simulation of nuclear fusion to detect disruptions before they happen in the real world. Just this week, we announced how Neural Operators can enable density functional theory simulation in quantum chemistry quasi-linear time. We have also used Neural Operators to invent better medical devices like a catheter that reduces bacterial contamination by 100x and we have been able to design better masks for chips and optimized gate layouts for quantum dots. More recently we have been asking ourselves what would happen if we aggressively scale our models and put multiple areas of physics in the same model, teaching it physics in full 4D (3D space + time). This requires massive scale and that is exactly what we have been able to do at Accelerated Understanding. We have pre-trained models up to 1 Trillion parameters, and we are able to train at 4D context lengths of up to 1 Trillion and run inference at 5 Trillion context. I am particularly excited about self-improvement: a limiting factor for scaling physical AI so far has been the availability of high quality training data. As the old saying goes: your model is only as good as your data. But that no longer holds true: for our models we have the laws of physics themselves that let us measure and improve the quality of our outputs exceeding what was present in the training data. But the improvement loop doesn’t stop at the models themselves. We can also use our models and their ability to understand physics and give directional feedback to break down one of the biggest barriers to innovation: the reliance on lab experiments as a bottleneck in the improvement loop. As intelligence gets more abundant this bottleneck is only increasing in importance. Putting our models and their physical simulation capabilities in that loop instead and taking advantage of their directional feedback means we only need the lab all the way in the end to double check. Excited to see new inventions and discoveries this will unlock! #TIME100AI#