Understanding how ecosystems respond to ubiquitous microplastic (MP) pollution is crucial for ensuring global food security. Here, we conduct a multiecosystem meta-analysis of 3,286 data points and reveal that MP exposure leads to a global reduction in photosynthesis of 7.05 to 12.12% in terrestrial plants, marine algae, and freshwater algae. These reductions align with those estimated by a constructed machine learning model using current MP pollution levels, showing that MP exposure reduces the chlorophyll content of photoautotrophs by 10.96 to 12.84%. Model estimates based on the identified MP-photosynthesis nexus indicate annual global losses of 4.11 to 13.52% (109.73 to 360.87 MT·y−1) for main crops and 0.31 to 7.24% (147.52 to 3415.11 MT C·y−1) for global aquatic net primary productivity induced by MPs. Under scenarios of efficient plastic mitigation, e.g.
Category: robotics/AI – Page 31
It’s about my paper.
Dissolving polymers with organic solvents is the essential process in the research and development of polymeric materials, including polymer synthesis, refining, painting, and coating. Now more than ever recycling plastic waste is a particularly imperative part of reducing carbon produced by the materials development processes.
Polymers, in this instance, refer to plastics and plastic-like materials that require certain solvents to be able to effectively dissolve and therefore become recyclable, though it’s not as easy as it sounds. Utilizing Mitsubishi Chemical Group’s (MCG) databank of quantum chemistry calculations, scientists developed a novel machine learning system for determining the miscibility of any given polymer with its solvent candidates, referred to as χ (chi) parameters.
This system has enabled scientists to overcome the limitations arising from a limited amount of experimental data on the polymer-solvent miscibility by integrating massive data produced from the computer experiments using high-throughput quantum chemistry calculations.
US tech giant OpenAI on Monday unveiled a ChatGPT tool called “deep research” that can produce detailed reports, as China’s DeepSeek chatbot heats up competition in the artificial intelligence field.
The company made the announcement in Tokyo, where OpenAI chief Sam Altman also trumpeted a new joint venture with tech investor SoftBank Group to offer advanced artificial intelligence services to businesses.
AI newcomer DeepSeek has sent Silicon Valley into a frenzy, with some calling its high performance and supposed low cost a wake-up call for US developers.
Current societal challenges exceed the capacity of humans operating either alone or collectively. As AI evolves, its role within human collectives will vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, together, can surpass the collective intelligence of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from complex network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising cognition, physical, and information layers.
AI models often rely on “spurious correlations,” making decisions based on unimportant and potentially misleading information. Researchers have now discovered these learned spurious correlations can be traced to a very small subset of the training data and have demonstrated a technique that overcomes the problem.
“This technique is novel in that it can be used even when you have no idea what spurious correlations the AI is relying on,” says Jung-Eun Kim, corresponding author of a paper on the work and an assistant professor of computer science at North Carolina State University.
“If you already have a good idea of what the spurious features are, our technique is an efficient and effective way to address the problem. However, even if you are simply having performance issues, but don’t understand why, you could still use our technique to determine whether a spurious correlation exists and resolve that issue.”
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In today’s AI news, ByteDance cofounder Zhang Yiming has become China’s richest man as investors bet on companies with AI potential. Zhang’s fortune has grown to $65.5 billion, ahead of beverage giant Nongfu Spring founder Zhong Shanshan’s $56.5 billion, according to Forbes estimates. Zhang, 41, derives his net worth from a 21% stake in the privately held tech behemoth …
And, OpenAI, Google, Meta, Microsoft, and smaller firms like Anthropic are losing massive amounts of money by giving away their AI products or selling them at a loss. “We are in the era of $5 Uber rides anywhere across San Francisco but for LLMs,” wrote early OpenAI engineer Andrej Karpathy. Chatbots are free, programming assistance is cheap, and attention-grabbing, money-losing AI toys are everywhere. AI is in its free(ish) trial era.
Meanwhile, the world’s largest contract electronics maker, Foxconn, said it has built its own large language model with reasoning capabilities, developed in-house and trained in four weeks. Initially designed for internal use within the company, the artificial-intelligence model, called FoxBrain, is capable of data analysis, mathematics, reasoning and code generation. Foxconn said Nvidia provided support …
Then, once upon a time, software ate the world. Now, AI is here to digest what’s left. The old model of computing, where apps ruled, marketplaces controlled access and platforms took their cut, is unraveling. What’s emerging is an AI-first world where software functions aren’t trapped inside apps but exist as dynamic, on-demand services accessible through AI-native interfaces.
In videos, learn how to integrate ElevenLabs Conversational AI platform with Cal. com for automated meeting scheduling. Angelo, takes you through the process with step-by-step instructions, and you can view and use the complete guide with Eleven Labs full documentation.
In other advancements, Anton Osika is the co-founder and CEO of Lovable, which is building what they call “the last piece of software”—an AI-powered tool that turns descriptions into working products without requiring any coding knowledge. Since launching three months ago, Lovable hit $4 million ARR in the first four weeks and $10 million ARR in two months with a team of just 15 people.
S first frame, influencing the entire clip. We We close out with, Jason Calacanis sitting down with Harrison Chase, CEO of LangChain, to explore how AI-powered agents are transforming the way startups operate. They discuss the shift from traditional entry-level roles to AI-driven automation, the importance of human-in-the-loop systems, and the future of AI-powered assistants in business. Harrison shares insights on how companies like Replit, Klarna, and GitLab are leveraging AI agents.
As Japan copes with a labor shortage, the service robot market is expected to triple in the next five years.
China is investing heavily in a new form of electronic warfare called cognitive EW but is the U.S. and rest of the world falling behind?
Berzerkers.
An exploration of what an alien robot might look like.
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