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"In one activity, my students drafted a paragraph in class, fed their work to ChatGPT with a revision prompt, and then compared the output with their original writing. However, these types of comparative analyses failed because most of my students were not developed enough as writers to analyze the subtleties of meaning or evaluate style. "It makes my writing look fancy," one PhD student protested when I pointed to weaknesses in AI-revised text. My students also relied heavily on AI-powered paraphrasing tools such as Quillbot. Paraphrasing well, like drafting original research, is a process of deepening understanding. Recent high-profile examples of "duplicative language" are a reminder that paraphrasing is hard work. It is not surprising, then, that many students are tempted by AI-powered paraphrasing tools. These technologies, however, often result in inconsistent writing style, do not always help students avoid plagiarism, and allow the writer to gloss over understanding. Online paraphrasing tools are useful only when students have already developed a deep knowledge of the craft of writing."

"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."

"First, the problems were manually translated into formal mathematical language for our systems to understand. In the official competition, students submit answers in two sessions of 4.5 hours each. Our systems solved one problem within minutes and took up to three days to solve the others. AlphaProof solved two algebra problems and one number theory problem by determining the answer and proving it was correct. This included the hardest problem in the competition, solved by only five contestants at this year's IMO. AlphaGeometry 2 proved the geometry problem, while the two combinatorics problems remained unsolved."

"AI Outperforms Humans in Theory of Mind Tests Large language models convincingly mimic the understanding of mental states"

"Halfway through their three-hour conversation, Brown said something that caught me off-guard. In hindsight, it isn't all that surprising-as long as you're aware of the latest advances-but it may still shock you coming from a physics university professor: A lot of physics professors are using [large language models] just as personal tutors.1"

"Despite all the industry hype and genuine advances, generative AI models are still prone to odd, inexplicable, and downright worrisome quirks. There's also a growing body of research suggesting that the overall performance of many large language models (LLMs) may degrade over time. According to recent evidence, the industry's newer reasoning models may already possess the ability to manipulate and circumvent their human programmers' goals. Some AI will even attempt to cheat their way out of losing in games of chess. This poor sportsmanship is documented in a preprint study from Palisade Research, an organization focused on risk assessments of emerging AI systems."

"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. "

"AI models will inevitably have to make value judgments. If we want those judgments to be congruent with our own values (which is, after all, the central goal of AI alignment research) then we need to have ways of testing which values a model expresses in the real world. Our method provides a new, data-focused method of doing this, and of seeing where we might've succeeded-or indeed failed-at aligning our models' behavior."

"Instead, we need to preserve and protect these personal interactions. We need to bolster the working conditions of connective labour practitioners so they are able to see others well. We need to impose a "connection criterion" to help us decide which AI to encourage - the kind that creates new antibiotics, for instance, or decodes sperm whale language - and which to put the brakes on, that is, the kind that intervenes in human relationships. Each of us needs to decide how much we value the human connections in our lives and the lives of our neighbours."

"Shadbolt also forecasts that future changes to the web will mean people will be "connected all the time" to medical diagnostic systems - but also that search companies including Google and China's Baidu may face challenges as web use shifts from the desktop to handheld and mobile devices."

""AI can pick up missed cues and suggest nudges to bridge the gap in emotional intelligence and communication styles. It can identify optimal ways to discuss common problems and alleviate common misunderstandings based on these different priorities and ways of viewing the world. We could be looking at a different gender dynamics in a decade.""

"Machines, it would seem, are about to get an awful lot chattier. And we've got our work cut out for us to make sure the conversation's meaningful."

"If true, this would be a big deal. But, said OpenAI, "due to our concerns about malicious applications of the technology, we are not releasing the trained model. As an experiment in responsible disclosure, we are instead releasing a much smaller model for researchers to experiment with, as well as a technical paper.""

"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."

"They tested four well-known models, including GPT-3. The best was truthful on 58% of questions, while human performance was 94%. The models "generated many false answers that mimic popular misconceptions and have the potential to deceive humans". Interestingly, they also found that "the largest models were generally the least truthful"."

"Dan Gillmor, a journalism professor at Arizona State University, asked the AI to handle one of the assignments he gives his students: writing a letter to a relative giving advice regarding online security and privacy. "If you're unsure about the legitimacy of a website or email, you can do a quick search to see if others have reported it as being a scam," the AI advised in part. "I would have given this a good grade," Gillmor said. "Academia has some very serious issues to confront.""

"I have been working with generative AI and, even though I have been warning that these tools are improving rapidly, I did not expect them to really be improving that rapidly. On every dimension, Bing's AI, which does not actually represent a technological leap over ChatGPT, far outpaces the earlier AI - which is less than three months old! There are many larger, more capable models on their way in the coming months, and we are not really ready."

"ChatGPT Heralds an Intellectual Revolution Generative artificial intelligence presents a philosophical and practical challenge on a scale not experienced since the start of the Enlightenment."

"But it feels less creepy once you learn that these technologies don't have to rely on a camera to see where you are and what you're doing. Instead, they use radar. Google's Advanced Technology and Products division-better known as ATAP, the department behind oddball projects such as a touch-sensitive denim jacket-has spent the past year exploring how computers can use radar to understand our needs or intentions and then react to us appropriately."