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In today’s AI news, ChatGPT just added 100 million users in two months, the fastest cohort adoption in two years, they said. As a result, we have increased our forecast for AI adoption in both consumer and enterprise, they added. OpenAI didn’t respond to a request for comment about what’s been driving this growth spurt. The Barclays analysts studying their growth suggested several reasons, though.

And, tech companies have been betting on virtual assistants for more than a decade, to little avail. But this new generation of AI was going to change things. But, the tech still doesn’t work. Chatbots may be fun to talk to and an occasionally useful replacement for Google, but truly game-changing virtual assistants are nowhere close to ready. And without them, the gadget revolution we were promised has utterly failed to materialize.

Meanwhile, AI company Sesame has released the base model that powers Maya, the impressively realistic voice assistant. The model, which is 1 billion parameters in size (“parameters” referring to individual components of the model), is under an Apache 2.0 license, meaning it can be used commercially with few restrictions. Called CSM-1B, the model generates “RVQ audio codes” from text and audio inputs.

S official forum, after producing approximately 750 to 800 lines of code, the AI assistant halted work and delivered a refusal message: “I cannot generate code for you, as that would be completing your work.” ‘ + In videos, can mislabeled dog paws ruin an AI model? IBM Fellow, Martin Keen explains how ground truth data ensures accurate AI predictions by powering supervised learning and training. Explore challenges like ambiguity and skewed data, and learn strategies to improve data labeling for better AI performance.

And, Harvey CEO Winston Weinberg explains why success in legal AI requires more than just model capabilities—it demands deep process expertise that doesn’t exist online. He shares how Harvey balances rapid product development with earning trust from law firms through hyper-personalized demos and deep industry expertise. He covers Harvey’s approach to product development—expanding specialized capabilities then collapsing them …

In further experimentation, Alex Ziskind compared running DeepSeek locally — various model sizes and quantizations on Apple Silicon M1, M2, M3, M4 Max MacBooks. Alex puts them all to the test and explains all the steps.

We close out with, Eric Simons is the founder and CEO of StackBlitz, the company behind Bolt—the #1 web-based AI coding agent and one of the fastest-growing products in history. After nearly shutting down, StackBlitz launched Bolt on Twitter and exploded from zero to $40 million ARR and 1 million monthly active users in about five months.

Continue reading “Why OpenAI’s Sam Altman Is Smiling: ChatGPT Has Kicked Into A Higher Gear” | >

With artificial photosynthesis, mankind could utilize solar energy to bind carbon dioxide and produce hydrogen. Chemists from Würzburg and Seoul have taken this one step further: They have synthesized a stack of dyes that comes very close to the photosynthetic apparatus of plants. It absorbs light energy, uses it to separate charge carriers and transfers them quickly and efficiently in the stack.

Photosynthesis is a marvelous process: plants use it to produce and oxygen from the simple starting materials carbon dioxide and water. They draw the energy they need for this complex process from sunlight.

If humans could imitate photosynthesis, it would have many advantages. The free energy from the sun could be used to remove carbon dioxide from the atmosphere and use it to build carbohydrates and other useful substances. It would also be possible to produce hydrogen, as photosynthesis splits water into its components oxygen and hydrogen.

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A research team led by Assistant Professor Shogo Mori and Professor Susumu Saito at Nagoya University has developed a method of artificial photosynthesis that uses sunlight and water to produce energy and valuable organic compounds, including pharmaceutical materials, from waste organic compounds. This achievement represents a significant step toward sustainable energy and chemical production.

The findings were published in Nature Communications.

“Artificial photosynthesis involves that mimic the way plants convert sunlight, water, and carbon dioxide into energy-rich glucose,” Saito explained. “Waste products, which are often produced by other processes, were not formed; instead, only energy and useful chemicals were created.”

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Humans can do plenty, but plants have an ability we don’t: they make energy straight from sunlight, a superpower called photosynthesis. Yet new research shows that scientists are closing that gap.

Osaka Metropolitan University researchers have revealed the 3D structure of an artificial photosynthetic antenna protein complex, known as light-harvesting complex II (LHCII), and demonstrated that the artificial LHCII closely mirrors its natural counterpart. This discovery marks a significant step forward in understanding how plants harvest and manage , paving the way for future innovations in artificial .

The researchers, led by Associate Professor Ritsuko Fujii and then graduate student Soichiro Seki of the Graduate School of Science and Research Center for Artificial Photosynthesis, had their study published in PNAS Nexus.

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Mankind is facing a central challenge: It must manage the transition to a sustainable and carbon dioxide-neutral energy economy.

Hydrogen is considered a promising alternative to fossil fuels. It can be produced from water using electricity. If the electricity comes from , it is called green . But it would be even more sustainable if hydrogen could be produced directly with the energy of sunlight.

In nature, light-driven water splitting takes place during photosynthesis in plants. Plants use a complex molecular apparatus for this, the so-called photosystem II. Mimicking its active center is a promising strategy for realizing the sustainable production of hydrogen. A team led by Professor Frank Würthner at the Institute of Organic Chemistry and the Center for Nanosystems Chemistry at Julius-Maximilians-Universität Würzburg (JMU) is working on this.

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Quantum systems hold the promise of tackling some complex problems faster and more efficiently than classical computers. Despite their potential, so far only a limited number of studies have conclusively demonstrated that quantum computers can outperform classical computers on specific tasks. Most of these studies focused on tasks that involve advanced computations, simulations or optimization, which can be difficult for non-experts to grasp.

Researchers at the University of Oxford and the University of Sevilla recently demonstrated a over a classical scenario on a cooperation task called the odd-cycle game. Their paper, published in Physical Review Letters, shows that a team with can win this game more often than a team without.

“There is a lot of talk about quantum advantage and how will revolutionize entire industries, but if you look closely, in many cases, there is no mathematical proof that classical methods definitely cannot find solutions as efficiently as quantum algorithms,” Peter Drmota, first author of the paper, told Phys.org.

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