Advanced materials are urgently needed for everyday life, be it in high technology, mobility, infrastructure, green energy or medicine. However, traditional ways of discovering and exploring new materials encounter limits due to the complexity of chemical compositions, structures and targeted properties. Moreover, new materials should not only enable novel applications, but also include sustainable ways of producing, using and recycling them.
Researchers from the Max-Planck-Institut für Eisenforschung (MPIE) review the status of physics-based modelling and discuss how combining these approaches with artificial intelligence can open so far untapped spaces for the design of complex materials.
They published their perspective in the journal Nature Computational Science (“Accelerating the design of compositionally complex materials via physics-informed artificial intelligence”).
10 SpaceX Starships are carrying 120 robots to Mars. They are the first to colonize the Red Planet. Building robot habitats to protect themselves, and then landing pads, structures, and the life support systems for the humans who will soon arrive.
This Mars colonization mini documentary also covers they type of robots that will be building on Mars, the solar fields, how Elon Musk and Tesla could have a battery bank station at the Mars colony, and how the Martian colony expands during the 2 years when the robots are building. Known as the Robotic Age of Mars.
Additional footage from: SpaceX, NASA/JPL/University of Arizona, ICON, HASSEL, Tesla, Lockhead Martin.
A building on Mars sci-fi documentary, and a timelapse look into the future.
See more of Venture City at my website: https://vx-c.com.
_______
Books.
• The Martian book showcases the science, math, and physics of living on the red planet — told through the story of someone who has to survive there.
Anti AI / AI ethics clowns now pushing.gov for some criminalization, on cue.
A nonprofit AI research group wants the Federal Trade Commission to investigate OpenAI, Inc. and halt releases of GPT-4.
OpenAI “has released a product GPT-4 for the consumer market that is biased, deceptive, and a risk to privacy and public safety. The outputs cannot be proven or replicated. No independent assessment was undertaken prior to deployment,” said a complaint to the FTC submitted today by the Center for Artificial Intelligence and Digital Policy (CAIDP).
Calling for “independent oversight and evaluation of commercial AI products offered in the United States,” CAIDP asked the FTC to “open an investigation into OpenAI, enjoin further commercial releases of GPT-4, and ensure the establishment of necessary guardrails to protect consumers, businesses, and the commercial marketplace.”
Derek Thompson published an essay in the Atlantic last week that pondered an intriguing question: “When we’re looking at generative AI, what are we actually looking at?” The essay was framed like this: “Narrowly speaking, GPT-4 is a large language model that produces human-inspired content by using transformer technology to predict text. Narrowly speaking, it is an overconfident, and often hallucinatory, auto-complete robot. This is an okay way of describing the technology, if you’re content with a dictionary definition.
He closes his essay with one last analogy, one that really makes you think about the-as-of-yet unforeseen consequences of generative AI technologies — good or bad: Scientists don’t know exactly how or when humans first wrangled fire as a technology, roughly 1 million years ago. But we have a good idea of how fire invented modern humanity … fire softened meat and vegetables, allowing humans to accelerate their calorie consumption. Meanwhile, by scaring off predators, controlled fire allowed humans to sleep on the ground for longer periods of time. The combination of more calories and more REM over the millennia allowed us to grow big, unusually energy-greedy brains with sharpened capacities for memory and prediction. Narrowly, fire made stuff hotter. But it also quite literally expanded our minds … Our ancestors knew that open flame was a feral power, which deserved reverence and even fear. The same technology that made civilization possible also flattened cities.
Thompson concisely passes judgment about what he thinks generative AI will do to us in his final sentence: I think this technology will expand our minds. And I think it will burn us.
Thompson’s essay inadvertently but quite poetically illustrates why it’s so difficult to predict events and consequences too far into the future. Scientists and philosophers have studied the process of how knowledge is expanded from a current state to novel directions of thought and knowledge.
This year’s NVIDIA GPU Technology Conference (GTC) could not have come at a more auspicious time for the company. The hottest topic in technology today is the Artificial Intelligence (AI) behind ChatGPT, other related Large Language Models (LLMs), and their applications for generative AI applications. Underlying all this new AI technology are NVIDIA GPUs. NVIDIA’s CEO Jensen Huang doubled down on support for LLMs and the future of generative AI based on it. He’s calling it “the iPhone moment for AI.” Using LLMs, AI computers can learn the languages of people, programs, images, or chemistry. Using the large knowledge base and based on a query, they can create new, unique works: this is generative AI.
Jumbo sized LLM’s are taking this capability to new levels, specifically the latest GPT 4.0, which was introduced just prior to GTC. Training these complex models takes thousands of GPUs, and then applying these models to specific problems require more GPUs as well for inference. Nvidia’s latest Hopper GPU, the H100, is known for training, but the GPU can also be divided into multiple instances (up to 7), which Nvidia calls MIG (Multi-Instance GPU), to allow multiple inference models to be run on the GPU. It’s in this inference mode that the GPU transforms queries into new outputs, using trained LLMs.
Nvidia is using its leadership position to build new business opportunities by being a full-stack supplier of AI, including chips, software, accelerator cards, systems, and even services. The company is opening up its services business in areas such as biology, for example. The company’s pricing might be based on use time, or it could be based on the value of the end product built with its services.
The release of ChatGPT in late November 2022 lit a fire under the subdued venture capital sector, a hesitant business community, and the work of academics and regulators. While venture funding decreased by 19% from Q3’22 to Q4’22, AI funding increased 15% over the same period, according to CB Insights’ State of AI 2022 Report (annual AI funding dropped by 34% in 2022, mirroring the broader venture funding downturn). Looking specifically at generative AI startups, CB Insights found that 2022 was a record year, with equity funding topping $2.6 billion across 110 deals.
Everywhere you turn, you encounter generative AI.
Generative AI, in concert with other quickly growing technologies, is propelling a revolutionary future, blurring the line between the digital and physical world, says Accenture’s new report.
When combined, cloud, metaverse, and AI trends will reduce the gap between the virtual and real worlds, according to the Fortune Global 500 tech company.