#Language Is The Next Great Frontier In AI - RSS -- Dec 13, 2023,10:00am EST Say AIIIIII: How AI Is Transforming Dentistry Dec 13, 2023,06:20am EST Key Lessons Involving Generative AI Mental Health Apps Via That Eating Disorders Chatbot Tessa Which Went Off The Rails And Was Abruptly -- Dec 12, 2023,09:31pm EST Artificial Intelligence, Quantum Computing, and Space are 3 Tech areas to Watch in 2024 -- Here’s How The Famous Dodo Verdict Or Tie Score Effect In Mental Health Therapy Can Astutely Leverage Generative AI Dec 10, 2023,09:34pm EST Advances In AI, Yet Many Unresolved Issues Dec 10, 2023,08:31pm EST How Accurate Were Our 2023 AI Predictions? Dec 8, 2023,02:36pm EST -- Language Is The Next Great Frontier In AI -- Opinions expressed by Forbes Contributors are their own. I write about the big picture of artificial intelligence. Following -- See here for the second part of this article series: A Wave Of Billion-Dollar Language AI Startups Is Coming __________________________________________________________________ -- Building machines that can understand language has thus been a central goal of the field of artificial intelligence dating back to its earliest days. -- This is because mastering language is what is known as an “AI-complete” problem: that is, an AI that can truly understand language the way a human can would by implication be capable of any other human-level intellectual activity. Put simply, to solve language is to solve AI. MORE FROMFORBES ADVISOR -- This profound and subtle insight is at the heart of the “Turing test,” introduced by AI pioneer Alan Turing in a groundbreaking 1950 paper. Though often critiqued or misunderstood, the Turing test captures a -- passed the Turing test.) But over the past few years researchers have achieved startling, game-changing breakthroughs in language AI, also called natural language processing (NLP). -- The most powerful way to illustrate the capabilities of today’s cutting-edge language AI is to start with a few concrete examples. Today’s AI can correctly answer complex medical queries—and explain the underlying biological mechanisms at play. It can craft nuanced memos -- What is behind these astonishing new AI abilities, which just five years ago would have been inconceivable? -- In short: the invention of the transformer, a new neural network architecture that has unleashed vast new possibilities in AI. -- analyzed at the same time rather than in sequence. In order to support this parallelization, transformers rely on an AI mechanism known as attention. Attention enables a model to consider the relationships -- A flurry of innovation followed in the wake of the original transformer paper as the world’s leading AI researchers built upon this foundational breakthrough. -- sheer size. OpenAI has been intentional and transparent about its strategy to pursue more advanced language AI capabilities through raw scale above all else: more compute, larger training data corpora, -- unlabeled data. This is a crucial difference between today’s cutting-edge language AI models and the previous generation of NLP models, which had to be trained with labeled data. Today’s -- new paradigm for NLP technology development—one that will have profound implications for the nascent AI economy. -- produce them, will exert outsize influence on the future behavior of artificial intelligence around the world. -- the foundation models can lead to immediate benefits across all of NLP), it is also a liability; all AI systems might inherit the same problematic biases of a few foundation models.” -- The source of social bias in AI models is straightforward to summarize but insidiously difficult to root out. Because large language models -- foundation models become increasingly influential in society. Some observers believe that AI bias will eventually become as prominent of an issue for consumers, companies and governments as digital threats -- There is no silver-bullet solution to the challenge of AI bias and toxicity. But as the problem becomes more widely recognized, a number -- Historically, Alphabet’s DeepMind has been an outlier among the world’s most advanced AI research organizations for not making language AI a major focus area. This changed at the end of 2021, with DeepMind -- Of the three NLP papers that DeepMind published, one is devoted entirely to the ethical and social risks of language AI. The paper proposes a comprehensive taxonomy of 6 thematic areas and 21 specific -- central focus of its NLP research going forward to help ensure that it is pursuing innovation in language AI responsibly. The fact that this dimension of language AI research—until recently, treated as an afterthought or ignored altogether by most of the world’s NLP researchers—featured so centrally in DeepMind’s recent foray into language AI may be a signal of the field’s shifting priorities moving forward. Increased regulatory focus on the harms of bias and toxicity in AI models will only accelerate this shift. And make no mistake: regulatory -- involve natural language at all. In particular, today’s cutting-edge language AI technology is powering remarkable breakthroughs in two other domains: coding and biology. -- It therefore makes sense that the same powerful new technologies that have given AI incredible fluency in natural language can likewise be applied to programming languages, with similar results. -- Then, just two weeks ago, DeepMind further advanced the frontiers of AI coding with its publication of AlphaCode. AlphaCode is an AI system that can compete at a human level in programming competitions. In these competitions, which attract hundreds -- with up to hundreds of lines of code. AlphaCode almost seems to display that ever-elusive attribute in AI, high-level reasoning. -- problems is second nature in human intelligence—a result of critical thinking informed by experience. For artificial intelligence to help humanity, our systems need to be able to develop problem-solving -- Another subfield of biology that represents fertile ground for language AI is the study of proteins. Proteins are strings of building blocks known as amino acids, linked together in a particular order. There are -- As one example, an AI research team from Salesforce recently built an NLP model that “learns the language of proteins” and can generate -- These efforts are just the beginning. In the months and years ahead, language AI will make profound contributions to our understanding of how life itself works. -- Language is at the heart of human intelligence. It therefore is and must be at the heart of our efforts to build artificial intelligence. No sophisticated AI can exist without mastery of language. Today, the field of language AI is at an exhilarating inflection point, on the cusp of transforming industries and spawning new -- This article explored the big-picture developments and trends shaping the world of language AI today. In a followup article, we canvass today’s most exciting NLP startups. A growing group of NLP entrepreneurs is applying cutting-edge language AI in creative ways across sectors and use cases, generating massive economic value and