Large Language Models (LLMs) entered the world stage with the release of OpenAI's GPT-3 in 2020 [GPT3]. Since then, they've enjoyed a steady growth in popularity. That is until late 2022. Interest in LLMs and the broader discipline of generative AI has skyrocketed. The reasons for this are likely the continuous upward momentum of significant advances in LLMs.

Graphs are a natural representation of brain activity derived from functional magnetic imaging (fMRI) data. It is well known that clusters of anatomical brain regions, known as functional connectivity networks (FCNs), encode temporal relationships which can serve as useful biomarkers for understanding brain function and dysfunction. Previous works, however, ignore the temporal dynamics of the brain and focus on static graphs. In this paper, we propose a dynamic brain graph deep generative model (DBGDGM) which simultaneously clusters brain regions into temporally evolving communities and learns dynamic unsupervised node embeddings. Specifically, DBGDGM represents brain graph nodes as embeddings sampled from a distribution over communities that evolve over time. We parameterise this community distribution using neural networks that learn from subject and node embeddings as well as past community assignments. Experiments demonstrate DBGDGM outperforms baselines in graph generation, dynamic link prediction, and is comparable for graph classification. Finally, an analysis of the learnt community distributions reveals overlap with known FCNs reported in neuroscience literature.

Developers are in the business of building world, so it's easy to understand why the games industry would be excited about generative AI. With computers doing the boring stuff, a small team could whip up a map the size of San Andreas. Crunch becomes a thing of the past; games release in a finished state. There are, at the very least, two interrelated problems with this narrative. First, there's the logic of the hype itself--reminiscent of the frenzied gold rush over crypto/Web3/the metaverse--that, consciously or not, seems to consider automating artists' jobs a form of progress. Back in November, when DALL-E was seemingly everywhere, venture capital firm Andreessen Horowitz posted a a long analysis on their website touting a "generative AI revolution in games" that would do everything from shorten development time to change the kinds of titles being made.

HOW would you feel if your doctor, rather than consult their own clinical knowledge, turned instead to an AI trained on your medical history to help diagnose your next ailment or write your next prescription? These sorts of scenarios have been hypothetical for decades – the technology has been subpar and the stakes too high to risk offloading medical advice to a machine. However, the success of large language models like ChatGPT, a popular, artificially intelligent chatbot from the OpenAI research lab, has led to a rethink of what might be possible.

ChatGPT, the AI chatbot developed by tech company OpenAI, can find and fix bugs in computer code as well as standard machine learning approaches – and does even better when engaged in conversation. Dominik Sobania at Johannes Gutenberg University in Mainz, Germany, and his colleagues sought to see how well ChatGPT compared with other AI-powered coding support tools. A number of tools exist that use artificial intelligence to check programming code to ensure there are no mistakes. "ChatGPT came out and we thought it seems …

I have a grayish dual position regarding generative art and, well, basically, generative creativity. One view is extremely cynical, and the other perspective is hopeful. I wrote earlier about this topic here (note: a bit gloomy). Let me start with the cynical view, hyperbolized for ease of communication. I see this as a big tech effort to lower tech wages, reduce negotiation positions of creative workers, push the commoditization of art, create a new scaleable consumer market, and more holistically drive society towards transhumanism.

The past several months have been turbulent for Microsoft. In December, its $69 billion deal to acquire the video game maker Activision was challenged by regulators in the United States, and last week it began laying off about 10,000 workers. On Monday, Microsoft announced a major new investment in OpenAI, the start-up behind ChatGPT and other generative artificial intelligence breakthroughs, and signaled plans to include A.I. in an array of Microsoft products. The biggest slowdown came from Microsoft's personal computing business, where sales fell 19 percent and operating income fell 47 percent. The business boomed during the first part of the pandemic.

Like many big tech companies, Microsoft is preparing for the worst after announcing plans to lay off 10,000 employees in the upcoming third quarter. It turns out that the company's second quarter was a mixed bag: It earned $52.7 billion in revenue, which was up 2 percent from last year, but a slight miss from the $52.9 billion analysts expected. Profits also fell by 12 percent to $16.4 billion, a trend that may continue throughout the year. Despite the faltering PC market, Microsoft has been riding high on cloud revenues for years, and that seems to be continuing. Microsoft's belt tightening didn't stop the company from potentially investing $10 billion more in ChatGPT creator OpenAI, yet another sign that AI is going to play a major role in its future projects. The company plans to add ChatGPT to its Azure OpenAI service soon, and it's reportedly planning to integrated that technology in Bing.

The fruit of more than a decade of research inside companies like OpenAI, Google and Meta, these technologies are poised to remake everything from online search engines like Google Search and Microsoft Bing to photo and graphics editors like Photoshop. The deal follows Microsoft's announcement last week that it had begun laying off employees as part of an effort to cull 10,000 positions. The changes, including severance, ending leases and what it called "changes to our hardware portfolio" would cost $1.2 billion, it said. Satya Nadella, the company's chief executive, said last week that the cuts would let the company refocus on priorities such as artificial intelligence, which he called "the next major wave of computing." Mr. Nadella made clear in his company's announcement on Monday that the next phase of the partnership with OpenAI would focus on bringing tools to the market, saying that "developers and organizations across industries will have access to the best A.I. infrastructure, models and tool chain."

From steam power and electricity to computers and the internet, technological advancements have always disrupted labor markets, pushing out some jobs while creating others. Artificial intelligence remains something of a misnomer – the smartest computer systems still don't actually know anything – but the technology has reached an inflection point where it's poised to affect new classes of jobs: artists and knowledge workers. Specifically, the emergence of large language models – AI systems that are trained on vast amounts of text – means computers can now produce human-sounding written language and convert descriptive phrases into realistic images. The Conversation asked five artificial intelligence researchers to discuss how large language models are likely to affect artists and knowledge workers. And, as our experts noted, the technology is far from perfect, which raises a host of issues – from misinformation to plagiarism – that affect human workers.