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"The announcement also highlights the growing partnership between Meta and Nvidia. Nvidia is a key Meta partner, providing the Facebook parent with computing chips called GPUs to help train its AI models, including the latest version of Llama."

"The climate crisis could prove AI's greatest challenge. While Google publicises AI-driven advances in flooding, wildfire and heatwave forecasts, like many big tech companies, it uses more energy than many countries. Today's large models are a major culprit. It can take 10 gigawatt-hours of power to train a single large language model like OpenAI's ChatGPT, enough to supply 1,000 US homes for a year."

"The research, conducted at Vision and AI Lab of the Department of Computational and Data Sciences, offers a novel approach to mitigating bias in popular image-generative models without the need for additional data or model retraining."

"The model takes a two-pronged approach. First, it focuses on trends present in the region, looking at geostatistics and historical data from Prodes, the annual government monitoring system for deforestation in the Amazon. Understanding what has happened can help make predictions more precise. When already deforested areas are recent, this indicates gangs are operating in the area, so there's a higher risk that nearby forest will soon be wiped out. Second, it looks at variables that put the brakes on deforestation - land protected by Indigenous and quilombola (descendent of rebel slaves) communities, and areas with bodies of water, or other terrain that doesn't lend itself to agricultural expansion, for instance - and variables that make deforestation more likely, including higher population density, the presence of settlements and rural properties, and higher density of road infrastructure, both legal and illegal."

"Most AI programs function like a "black box." "We know exactly what a model does but not why it has now specifically recognized that a picture shows a cat," said computer scientist Kristian Kersting of the Technical University of Darmstadt in Germany to the German-language newspaper Handelsblatt. That dilemma prompted Kersting-along with computer scientists Patrick Schramowski of the Technical University of Darmstadt and Björn Deiseroth, Mayukh Deb and Samuel Weinbach, all at the Heidelberg, Germany-based AI company Aleph Alpha-to introduce an algorithm called AtMan earlier this year. AtMan allows large AI systems such as ChatGPT, Dall-E and Midjourney to finally explain their outputs."

"One of the key features introduced is a "Correction" capability in Azure AI Content Safety. This tool aims to address the problem of AI hallucinations - instances where AI models generate false or misleading information. "When we detect there's a mismatch between the grounding context and the response… we give that information back to the AI system," Bird explained. "With that additional information, it's usually able to do better the second try.""

"People have made the anecdotal observation that their Apple products become much slower right before the release of a new model. Now, a Harvard University study has done what any person with Google Trends could do, and pointed out that Google searches for "iPhone slow" spiked multiple times, just before the release of a new iPhone each time."

"It's not that Google wants to do this, it's that they didn't anticipate this outcome, and compounded that omission by likewise omitting a way to overrule the algorithm's judgment. As with other examples of algorithmic cruelty, it's not so much this specific example as was it presages for a future in which more and more of our external reality is determined by models derived from machine learning systems whose workings we're not privy to and have no say in. "

"Amid mounting financial pressure, at least a dozen police forces are using or considering predictive analytics, despite warnings from campaigners that use of algorithms and "predictive policing" models risks locking discrimination into the criminal justice system."

"he outlines three sources of dysfunction - 'deliberate, malicious intent, such as state-sponsored hacking and attacks, criminal behaviour, and online harassment'; 'system design' which has created 'perverse incentives where user value is sacrificed, such as ad-based revenue models that commercially reward clickbait'; and the 'viral spread of misinformation'. he also calls attention to the 'unintended negative consequences' of the web, which he said had led to 'the outraged and polarised tone and quality of online discourse'."

"Researchers showed detectors can be defeated by inserting inputs called adversarial examples into every video frame. The adversarial examples are slightly manipulated inputs which cause artificial intelligence systems such as machine learning models to make a mistake. In addition, the team showed that the attack still works after videos are compressed."

"These experiments in computational creativity are enabled by the dramatic advances in deep learning over the past decade. Deep learning has several key advantages for creative pursuits. For starters, it's extremely flexible, and it's relatively easy to train deep-learning systems (which we call models) to take on a wide variety of tasks."

"Green Light uses machine learning systems to comb through Maps data to calculate the amount of traffic congestion present at a given light, as well as the average wait times of vehicles stopped there. That information is then used to train AI models that can autonomously optimize the traffic timing at that intersection, reducing idle times as well as the amount of braking and accelerating vehicles have to do there. It's all part of Google's goal to help its partners collectively reduce their carbon emissions by a gigaton by 2030."

"The new AI Index report notes that in 2023, AI still struggled with complex cognitive tasks like advanced math problem-solving and visual commonsense reasoning. However, 'struggled' here might be misleading; it certainly doesn't mean AI did badly. Performance on MATH, a dataset of 12,500 challenging competition-level math problems, improved dramatically in the two years since its introduction. In 2021, AI systems could solve only 6.9% of problems. By contrast, in 2023, a GPT-4-based model solved 84.3%. The human baseline is 90%. "

"Ultimately, he suggests, each user would have their own "large language model" (LLM), the underlying technology of services such as ChatGPT, which would be trained on their own speech and behaviour patterns, to let them generate extremely personalised responses to queries and requests. Such systems could be a natural progression from AI tools that already exist today. Services such as Gmail can summarise and suggest replies to emails based on previous messages, while Microsoft Teams will transcribe and summarise video conferences, automatically generating a to-do list from the contents."

"First, the drones engage in aerial mapping to create detailed three-dimensional terrain models. They then begin "precision planting" by shooting seed pods that have been "pregerminated and covered in a nutritious hydrogel" into the soil. Finally, drones monitor tree growth over the course of a number of "planting audits," designed to track the reforrestation progress. "

"The use for humans in the world of robotics, even as teachers, is shrinking thanks to AI. NVIDIA Research has announced the creation of Eureka, an AI agent powered by GPT-4 that has trained robots to perform tasks using reward algorithms. Notably, Eureka taught a robotic hand to do pen spinning tricks as well as a human can (honestly, as you can see in the YouTube video below, better than many of us)."

"Imagine sitting down with an AI model for a spoken two-hour interview. A friendly voice guides you through a conversation that ranges from your childhood, your formative memories, and your career to your thoughts on immigration policy. Not long after, a virtual replica of you is able to embody your values and preferences with stunning accuracy. That's now possible, according to a new paper from a team including researchers from Stanford and Google DeepMind, which has been published on arXiv and has not yet been peer-reviewed."

"Brands such as fintech company Ramp, jobs search site Indeed and Pernod Ricard-owned Scottish whisky maker Chivas Brothers have adopted the software. They are hoping to reach millions of users who regularly use generative AI products as a new method to search for information online - a shift that poses a long-term threat for Google's main business. "This is about much more than just getting your website indexed in their results. This is about recognising large language models as the ultimate influencer," said Jack Smyth, partner at marketing technology group Brandtech, which has created its own interface for brands. "