As artificial intelligence devours electricity, a quiet nuclear revolution is taking shape deep below future data centers.
Across Europe, tech firms are staring at an uncomfortable equation: soaring digital demand, power grids near saturation, and climate goals that leave little room for more fossil fuels. A young French company now claims it can rewrite that equation with a compact reactor that hides underground and feeds on nuclear waste.
Thousands of Amazon employees have signed an open letter issuing some dire warnings about the company’s move toward AI. The letter, signed by more than 1,000 workers (and counting) calls out Amazon for pushing its AI investments at the expense of the climate and its human workforce. The letter’s supporters come from a wide array of roles at the company, including many software engineers, and even employees focused on building AI systems. “We believe that the all-costs-justified, warp-speed approach to AI development will do staggering damage to democracy, to our jobs, and to the earth,” the letter’s authors wrote. It adds, “We’re the workers who develop, train, and use AI, so we have a responsibility to intervene.”
Over a thousand Amazon employees have penned an open letter, warning that the company’s rapid AI development is jeopardizing its climate commitments and human workforce. They argue the pursuit of AI dominance is leading to increased emissions, water scarcity, and job displacement, urging leadership to prioritize ethical AI and environmental responsibility.
When describing collective properties of macroscopic physical systems, microscopic fluctuations are typically averaged out, leaving a description of the typical behavior of the systems. While this simplification has its advantages, it fails to capture the important role of fluctuations that can often influence the dynamics in dramatic manners, as the extreme examples of catastrophic events such as volcanic eruptions and financial market collapse reveal.
On the other hand, studying the dynamics of individual microscopic degrees of freedom comprehensively becomes too cumbersome even when considering systems of a moderate number of particles. To describe the interface between these opposite ends of the scale, stochastic field theories are commonly used to characterize the dynamics of complex systems and the effect of the microscopic fluctuations.
Due to their overwhelming complexity, predicting outcomes by analyzing these fluctuations in living or active matter systems is not possible using traditional methods of physics. Since these systems persistently consume energy, they exhibit dynamical traits that violate the laws of equilibrium thermodynamics, not unrelated to the arrow of time.
From the rise of numerical and symbolic computing to the future of AI, this talk traces five decades of breakthroughs and the challenges ahead.
Bill is the author of Berkeley UNIX, cofounder of Sun Microsystems, author of “Why the Future Doesn’t Need Us” (Wired 2000), ex-cleantech VC at Kleiner Perkins, investor in and unpaid advisor to Nodra. AI.
Talk Details.
50 Years of Advancements: Computing and Technology 1975–2025 (and beyond)
I came to UC Berkeley CS in 1975 as a graduate student expecting to do computer theory— Berkeley CS didn’t have a proper departmental computer, and I was tired of coding, having written a lot of numerical code for early supercomputers.
But it’s hard to make predictions, especially about the future. Berkeley soon had a Vax superminicomputer, I installed a port of UNIX and was upgrading the operating system, and the Internet and Microprocessor boom beckoned.
Globalization, migration, climate change and war—nation states are currently under huge pressure on many fronts. Understanding the forces that initially drove the emergence of states across the world may help explain why.
For a long time after humans evolved, we lived in oral-based, mostly small-scale and egalitarian societies. Things began to change with the dawn of the Holocene, when a suite of climatic, social and technological shifts led to the emergence of the first states about 5,000 years ago.
The earliest known state was in Mesopotamia (now southern Iraq), followed by Egypt, the Indus Valley, China and Meso-America. The long-standing view was that the invention of agriculture was the spur for these large-scale human societies to emerge. But there was a 4,000-year gap between the expansion of agriculture (circa 9,000 years ago) and the founding of the earliest states, which throws this link into question.
Iron-nitrogen-carbon catalysts have the potential to replace the more expensive platinum catalysts currently used in fuel cells. This is shown by a study conducted by researchers from the Helmholtz-Zentrum Berlin (HZB), Physikalisch-Technische Bundesanstalt (PTB) and universities in Tartu and Tallinn, Estonia. The research is published in the journal ACS Nano.
At BESSY II, the team observed the formation of complex microstructures within various samples. They then analyzed which structural parameters were particularly important for fostering the preferred electrochemical reactions. The raw material for such catalysts is well decomposed peat.
Fuel cells convert the chemical energy of hydrogen directly into electrical energy, producing only water. Fuel cells could be an important component in a climate-neutral energy system. The greatest potential for improvement lies in the reduction of costs via the replacement of the electrocatalysts, which are currently based on the precious metal platinum.
About the size of a full-size pickup truck, a newly launched satellite by NASA and its partners will provide ocean and atmospheric information to improve hurricane forecasts, help protect infrastructure, and benefit commercial activities, such as shipping.
The Sentinel-6B satellite lifted off aboard a SpaceX Falcon 9 rocket from Launch Complex 4 East at Vandenberg Space Force Base in central California at 9:21 p.m. PST on Nov. 16. Contact between the satellite and a ground station in northern Canada occurred about 1 hour and 30 minutes later at 10:54 p.m. All systems are functioning normally.
“Understanding tidal patterns down to the inch is critical in protecting how we use our oceans every day on Earth,” said Nicky Fox, associate administrator, Science Mission Directorate at NASA Headquarters in Washington. “Sentinal-6B will build upon the legacy of Sentinel-6 Michael Freilich by making sea level measurements that improve forecasts used by communities, businesses, and operations across the country. It also will support a safer reentry for our astronauts returning home, including crew from Artemis Moon missions.”
Tropical cyclones can unleash extensive devastation, as recent storms that swept over Jamaica and the Philippines made unmistakably clear. Accurate weather forecasts that buy more time to prepare are crucial for saving lives and are rooted in a deeper understanding of climate systems.
Driving this forward, researchers at the Institute of Science and Technology Austria (ISTA) and others have successfully identified a previously unknown cyclic climate pattern by historical reanalysis of datasets and satellite observations. The findings are published in PNAS.
Jiawei Bao still remembers coming home from middle school to catch the weather forecast on TV. It spanned from China’s northernmost province, Heilongjiang, to the southernmost province and tropical island, Hainan. In winter, the temperature between these regions can range from cold to balmy, varying by a staggering 50 degrees Celsius.
Despite continuous efforts to evaluate and predict changes in Earth’s climate, most models still struggle to accurately simulate extreme precipitation events. Models like the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6) use fairly coarse resolution due to computing constraints, making it a little easier, faster and less expensive to run simulations, while still providing some degree of accuracy.
However, a new study, published in Nature Geoscience, is shedding light on some of the features missed by these coarser resolution models.
The team involved in the study developed a higher resolution model that breaks up the atmosphere into 10–25 km (6–15.5 mile) squares for analysis, instead of 100 km (62 mile) squares. Their high-resolution model is based on the Community Earth System Model v.1.3 (CESM-HR), which looks at the time period between 1920–2100. These results are then compared with the low-resolution version’s (CESM-LR) results.