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Generative AI could saddle the planet with heaps more hazardous waste.

By Saima S. Iqbal

Every time generative artificial intelligence drafts an e-mail or conjures up an image, the planet pays for it. Making two images can consume as much energy as charging a smartphone; a single exchange with ChatGPT can heat up a server so much that it requires a bottle’s worth of water to cool. At scale, these costs soar. By 2027, the global AI sector could annually consume as much electricity as the Netherlands, according to one recent estimate. And a new study in Nature Computational Science identifies another concern: AI’s outsize contribution to the world’s mounting heap of electronic waste. The study found that generative AI applications alone could add 1.2 million to five million metric tons of this hazardous trash to the planet by 2030, depending on how quickly the industry grows.

AI-human collaboration could possibly achieve superhuman greatness in mathematics.

By Conor Purcell

Mathematicians explore ideas by proposing conjectures and proving them with theorems. For centuries, they built these proofs line by careful line, and most math researchers still work like that today. But artificial intelligence is poised to fundamentally change this process. AI assistants nicknamed “co-pilots” are beginning to help mathematicians develop proofs—with a real possibility this will one day let humans answer some problems that are currently beyond our mind’s reach.

Is the chemical toxic?

While the scientists are unsure about the toxicity of the chemical, it is concerning since chloronitramide anion bears resemblance to other chemicals that are toxic in nature. David Wahman, one of the study’s authors and a research environmental engineer at the Environmental Protection Agency, said, “It has similarity to other toxic molecules. We looked for it in 40 samples in 10 US chlorinated drinking water systems located in seven states. We did find it in all the samples.”

Although almost everyone in the world now breathes air that is polluted in some way, the unfolding story of air pollution is one of environmental inequality.

Every time Mithilesh turns on her stove to cook, her eyes begin to burn. The small home the 29-year-old housewife shares with her husband, daughter, son and elderly in-laws in the slums of the Indian capital Delhi quickly fills up with smoke, making it hard for anyone to see.

Mithilesh has cooked over a traditional chulha – a metal coated combustor stove that uses firewood as fuel – since she was 13 years old. She often has difficulty breathing and experiences uncontrolled bouts of coughing.

The drug lorlatinib (Lorbrena) is superior to crizotinib (Xalkori) as an initial treatment for people with advanced non-small cell lung cancer (NSCLC) that has changes in the ALK gene, according to new results from a global clinical trial.

The findings are the latest from the CROWN study. Participants were randomly assigned to receive either lorlatinib or crizotinib as a treatment for advanced lung tumors with ALK gene mutations, a disease called ALK-positive lung cancer.

Several years ago, study investigators reported that participants who received lorlatinib went longer without the disease worsening, known as progression-free survival, than those who received crizotinib.

We’ll break down the key points of the patents and make them as understandable as possible. This new patent is likely how Tesla will implement FSD on non-Tesla vehicles, Optimus, and other devices.

Decision Making

Imagine a neural network as a decision-making machine. But building one also requires making a series of decisions about its structure and data processing methods. Think of it like choosing the right ingredients and cooking techniques for a complex recipe. These choices, called “decision points,” play a crucial role in how well the neural network performs on a given hardware platform.

MIT physicists have taken a key step toward solving the puzzle of what leads electrons to split into fractions of themselves. Their solution sheds light on the conditions that give rise to exotic electronic states in graphene and other two-dimensional systems.

The new work is an effort to make sense of a discovery that was reported earlier this year by a different group of physicists at MIT, led by Assistant Professor Long Ju. Ju’s team found that electrons appear to exhibit “fractional charge” in pentalayer graphene — a configuration of five graphene layers that are stacked atop a similarly structured sheet of boron nitride.

Ju discovered that when he sent an electric current through the pentalayer structure, the electrons seemed to pass through as fractions of their total charge, even in the absence of a magnetic field. Scientists had already shown that electrons can split into fractions under a very strong magnetic field, in what is known as the fractional quantum Hall effect. Ju’s work was the first to find that this effect was possible in graphene without a magnetic field — which until recently was not expected to exhibit such an effect.