Lamar wants to have children with his girlfriend. L amar remembered the moment of betrayal like it was yesterday. He'd gone to the party with his girlfriend but hadn't seen her for over an hour, and it wasn't like her to disappear. He slipped down the hallway to check his phone. At that point, he heard murmurs coming from one of the bedrooms and thought he recognised his best friend Jason's low voice. As he pushed the door ajar, they were both still scrambling to throw their clothes on; her shirt was unbuttoned, while Jason struggled to cover himself. The image of his girlfriend and best friend together hit Lamar like a blow to the chest. He left without saying a word. Two years on, when he spoke to me, the memory remained raw. He was still seething with anger, as if telling the story for the first time.

With the rise of AI, there has been an increased focus on global education. As the world becomes more interconnected, it is important for students to be able to learn about different cultures and perspectives. AI can help to provide students with a more comprehensive education by providing access to a wealth of information from around the world. In addition, it can help to customize learning experiences to individual students, making sure that each student receives the best possible education. As AI continues to evolve, it will likely have an even greater impact on education, making it more accessible and effective than ever before.

In this blog post, I touch on topics I will cover in depth in Win the War for AI Talent, currently scheduled for publication on June 27, 2022. Most large enterprises begin their AI transformation by hiring a few data scientists to build prototype models. The AI leaders quickly realize they need to make many other foundational changes to realize the company's AI vision. The big, obvious changes might be building an MLOps infrastructure and creating a new ML governance model. On top of those changes, they also need to handle the million little details and challenges that surface every day.

Abstractive dialogue summarization is a challenging task for several reasons. First, most of the important pieces of information in a conversation are scattered across utterances through multi-party interactions with different textual styles. Second, dialogues are often informal structures, wherein different individuals express personal perspectives, unlike text summarization, tasks that usually target formal documents such as news articles. To address these issues, we focused on the association between utterances from individual speakers and unique syntactic structures. Speakers have unique textual styles that can contain linguistic information, such as voiceprint. Therefore, we constructed a syntax-aware model by leveraging linguistic information (i.e., POS tagging), which alleviates the above issues by inherently distinguishing sentences uttered from individual speakers. We employed multi-task learning of both syntax-aware information and dialogue summarization. To the best of our knowledge, our approach is the first method to apply multi-task learning to the dialogue summarization task. Experiments on a SAMSum corpus (a large-scale dialogue summarization corpus) demonstrated that our method improved upon the vanilla model. We further analyze the costs and benefits of our approach relative to baseline models.

With so many novel drug candidates for Alzheimer's disease failing in clinical development, researchers in the US have started using artificial intelligence (AI) to screen already-approved therapies for activity against the neurodegenerative disorder. A team based at Massachusetts General Hospital and Harvard Medical School has come up with an AI algorithm – called DRIAD (Drug Repurposing In Alzheimer's Disease) – that it hopes will not only find treatments but also tease out new therapeutic targets. The AI uses machine learning to measure what happens to human brain neural cells when treated with a drug, and could be "a more rapid and less expensive option" than clinical trials of novel therapeutics, according to the researchers. In the journal Nature Communications, Harvard informatics specialist Artem Sokolov and colleagues report that early studies with the platform based on 80 approved drugs suggest Eli Lilly's Olumiant (baricitinib) as a possible candidate for repurposing as an AD therapy. It's not the first time that AI has suggested a new role for Olumiant, which is approved as an arthritis drug.

Late one January afternoon, British pharmacologist Peter Richardson ran out of his home office and told his wife, "Got it!" She asked what he was talking about and offered a cup of tea. Richardson explained that he had identified a drug that might help people infected with a new virus spreading in China. Richardson's dash was prompted by a finding from artificial intelligence software developed by his employer, BenevolentAI, a London startup where he is vice president of pharmacology. The company has created a kind of search engine on steroids that combines drug industry data with nuggets gleaned from scientific research papers.

The importance of artificial intelligence and machine learning (AI/ML) has not been lost on drug development companies. Recently, to help accelerate the discovery of therapies to treat COVID-19, several deals have been established to help deploy those tools. For example, Abcellera Biologics Inc., of Vancouver, British Columbia, and Eli Lilly and Co., of Indianapolis, agreed to co-develop antibody products for treating and preventing COVID-19. The collaboration will build on Abcellera's pandemic response platform, developed under the DARPA Pandemic Prevention Platform (P3) program, and Lilly's global capabilities for rapid development, manufacturing and distribution of therapeutic antibodies. Within one week of receiving a blood sample from one of the first U.S. patients who recovered from COVID-19, Abcellera screened more than 5 million immune cells looking for those that produced functional antibodies that helped the patient neutralize the virus and recover from the disease and identified more than 500 unique fully human antibody sequences.

Robots are attractive to pharmaceutical companies because they're "relentless…they never stop," says Peter Harris, chief executive of HighRes Biosolutions, a Beverly, Mass.,-based company that supplies automated systems for pharmaceutical clients. The software that controls the machines "is able to keep track of many more things in parallel than a human." Lilly recently put $90 million into a new 300,000-square-foot research center in San Diego, where robots are helping to speed up the pace of scientific discovery. In one installation, four glass-enclosed robotic arms grow cells, isolate DNA, and place samples into roughly postcard-sized plastic "plates" that resemble miniature muffin trays. They also shuttle these between various equipment, like measuring machines and incubators, said Dan Skovronsky, president of Lilly's research labs.

John C. Lilly is one of my favorite "alternative" scientists. His popularity has waned significantly since his death in 2001, even as his contemporaries like Timothy Leary and Terence McKenna have continued to have strong followings. Still, Lilly's admittedly outrageous ideas and prophecies are worth remembering, not because they are necessarily true, but because, like [...]

When I first talked with Anders Gustafsson and Erik Zaring in 2012, they promised their creepy, psychedelic, stop-motion game, The Dream Machine, was going to be "better than sex with Jesus." They had a lot of work ahead of them -- they were building the game by hand, with physical materials, and the stop-motion process was inherently time-consuming. Plus, they had to wrangle episodic installments of an intimate yet sprawling story inspired by LSD trips and theories of alternate realities. Five years later, as the sixth and final installment of The Dream Machine finally lands on Steam, I ask Gustafsson and Zaring if they think their game delivers on its sacrilegious promise. "I think we under-promised and over-delivered as far as sexual congress with the lord and savior is concerned," Gustafsson says.