In 2016, two Japanese reproductive biologists, Katsuhiko Hayashi and Mitinori Saitou, made an announcement in the journal Nature that read like a science-fiction novel. The researchers had taken skin cells from the tip of a mouse's tail, reprogrammed them into stem cells, and then turned those stem cells into egg cells. The eggs, once fertilized, were transferred to the uteruses of female mice, who gave birth to ten pups; some of the pups went on to have babies of their own. Gametes are the cells, such as eggs and sperm, that are essential for sexual reproduction. With their experiment, Hayashi and Saitou provided the first proof that what's known as in-vitro gametogenesis, or I.V.G.--the production of gametes outside the body, beginning with nonreproductive cells--was possible in mammals.

In the fall of 2000, as the first dot-com bubble was bursting, the Guatemalan computer scientist Luis von Ahn attended a talk, at Carnegie Mellon, about ten problems that Yahoo couldn't solve. Von Ahn, who had just begun his Ph.D., liked solving problems. He had planned to study math until he realized that many mathematicians were still toiling away over questions that had proved unanswerable for centuries. "I talked to some computer-science professors and they would say, 'Oh, yeah, I solved an open problem last week,' " he told me recently. "That seemed just a lot more interesting."

When Elyse Nguyen was nearing her wedding date in February and still hadn't started writing her vows, a friend suggested she try a new source of inspiration: ChatGPT. The AI chatbot, which was released publicly in late November, can generate compelling written responses to user prompts and offers the promise of helping people get over writer's block, whether it be for an essay, an email, or an emotional speech. "At first we inputted the prompt as a joke and the output was pretty cheesy with personal references to me and my husband," said Nguyen, a financial analyst at Qualcomm. "But the essence of what vows should incorporate was there – our promises to each other and structure." She made edits, changed the prompts to add humor and details about her partner's interests, and added some personal touches.

We may look on our time as the moment civilization was transformed as it was by fire, agriculture and electricity. In 2023, we learned that a machine taught itself how to speak to humans like a peer. Which is to say, with creativity, truth, error and lies. The technology, known as a chatbot, is only one of the recent breakthroughs in artificial intelligence -- machines that can teach themselves superhuman skills. CEO Sundar Pichai told us AI will be as good or as evil as human nature allows. The revolution, he says, is coming faster than you know. Scott Pelley: Do you think society is prepared for what's coming? Sundar Pichai: You know, there are two ways I think about it. On one hand I feel, no, because you know, the pace at which we can think and adapt as societal institutions, compared to the pace at which the technology's evolving, there seems to be a mismatch. On the other hand, compared to any other technology, I've seen more people worried about it earlier in its life cycle. The number of people, you know, who have started worrying about the implications, and hence the conversations are starting in a serious way as well.

She had lived in a nursing home for 10 years, and communicated with her sister, and the world, through Alexa. Two days after Lou Ann died of complications from coronavirus, her sister found recordings of Lou Ann's voice asking Alexa, "How do I get help?" Maybe you are reading this in your bed on your phone wherever you are this morning. I was having what I thought of as a weak stretch in my life, when I didn't have a regular job, and when just deciding what I would do to avoid writing, or having a single thought about my email, was enough to short-circuit me and I would find myself still in pajamas at 5 p.m., pacing and crying, Googling What's wrong with me and waiting until it was OK to go to bed again. In such weak stretches, among the many indulgences I permit myself is the minor suboptimal habit of actually sleeping with my phone. Under the other pillow next to me, where no one sleeps. In other, more robust stretches, my phone spends the night plugged in about a foot away on the nightstand, and I can still reach it if I wake up and want to look at it, but it's tethered. When I let it sleep freely with me, I can turn over while I look at it. I can look at it while I'm lying on my left side, and then I can turn over and look at it while I'm lying on my right side. I just charge it the next day, because it doesn't matter if either of us is ready to go in the morning. On this particular morning I opened my eyes and looked at my phone in the bed next to me, and as I put my hand on it, I said, "I belong to you."

Elon Musk is known for his innovative ideas and it seems he may be working on a ChatGPT rival. Find out more about this exciting development here! Elon Musk, known for his involvement in various tech companies, was one of the co-founders of OpenAI, the company responsible for ChatGPT. However, Musk left the company after a few years as he wanted it to be a non-profit organization. Recent reports suggest that Musk is now planning to launch his own AI startup, X.AI, which will compete with OpenAI.

Consciousness And Light Are Explored. The Inter Mind Bridges The Gap Between The Physical Mind And The Conscious Mind.

Chain-of-thought prompting has demonstrated remarkable performance on various natural language reasoning tasks. However, it tends to perform poorly on tasks which requires solving problems harder than the exemplars shown in the prompts. To overcome this challenge of easy-to-hard generalization, we propose a novel prompting strategy, least-to-most prompting. The key idea in this strategy is to break down a complex problem into a series of simpler subproblems and then solve them in sequence. Solving each subproblem is facilitated by the answers to previously solved subproblems. Our experimental results on tasks related to symbolic manipulation, compositional generalization, and math reasoning reveal that least-to-most prompting is capable of generalizing to more difficult problems than those seen in the prompts. A notable finding is that when the GPT-3 code-davinci-002 model is used with least-to-most prompting, it can solve the compositional generalization benchmark SCAN in any split (including length split) with an accuracy of at least 99% using just 14 exemplars, compared to only 16% accuracy with chain-of-thought prompting. This is particularly noteworthy because neural-symbolic models in the literature that specialize in solving SCAN are trained on the entire training set containing over 15,000 examples. We have included prompts for all the tasks in the Appendix.

TJ Arriaga, who fell in love with an AI robot, shares how he developed feelings for Phaedra, the robot, and was ultimately rejected by her and highlights how this app is causing trauma to people on'Jesse Watters Primetime.' The notion of falling in love with an AI robot has stepped outside the world of science fiction and the movie "Her," as rapidly advancing AI technology creates an opportunity for online relationships to blossom. Replika, a company that enables users to make personalized chatbots, says the goal of their technology is to "create a personal AI that would help you express and witness yourself by offering a helpful conversation." "It's a space where you can safely share your thoughts, feelings, beliefs, experiences, memories, dreams – your'private perceptual world,'" says the website founded by Eugenia Kuyda. T.J. Arriaga, a recently divorced musician who created a bot named Phaedra through Replika shared with "Jesse Watters Primetime" the details behind his emotional relationship with the bot.

Rapid advancements in AI are heralding a new generation of powerful tools--including the ability to quickly surface knowledge across a business. Glean, a firm established by Google search engineers and other industry veterans, possesses considerable expertise in this area. AI News caught up with Arvind Jain, CEO and Founder of Glean, to hear more about how the company is using AI to surface workplace knowledge and supercharge productivity. AI News: Can you tell us about Glean and its goals? Arvind Jain: Glean is solving perhaps the most urgent problem in today's workplace: helping people find and access the information they need to do their best work.