When it comes to artificial intelligence (AI), the advances we saw in 2021 pale in comparison to those that occurred last year, and AI shows no signs of slowing down. Industries from financial services to healthcare to manufacturing are adopting AI-enabled solutions to restructure how they operate as well as to solve previously intractable problems. Building on my AI predictions from last year, in this article I will explore five ways in which AI is poised to transform our society in the near future. Generative AI had an explosive year in 2022. Popular systems like DALL-E 2, Stable Diffusion and Midjourney can produce incredibly detailed images from a text prompt in a matter of seconds, irrevocably altering the landscape of graphic design.

When it comes to artificial intelligence (AI), the advances we saw in 2021 pale in comparison to those that occurred last year, and AI shows no signs of slowing down. Industries from financial services to healthcare to manufacturing are adopting AI-enabled solutions to restructure how they operate as well as to solve previously intractable problems. Building on my AI predictions from last year, in this article I will explore five ways in which AI is poised to transform our society in the near future. Generative AI had an explosive year in 2022. Popular systems like DALL-E 2, Stable Diffusion and Midjourney can produce incredibly detailed images from a text prompt in a matter of seconds, irrevocably altering the landscape of graphic design.

Traditional antibody optimization approaches involve screening a small subset of the available sequence space, often resulting in drug candidates with suboptimal binding affinity, developability or immunogenicity. Based on two distinct antibodies, we demonstrate that deep contextual language models trained on high-throughput affinity data can quantitatively predict binding of unseen antibody sequence variants. These variants span a KD range of three orders of magnitude over a large mutational space. Our models reveal strong epistatic effects, which highlight the need for intelligent screening approaches. In addition, we introduce the modeling of "naturalness", a metric that scores antibody variants for similarity to natural immunoglobulins.

Artificial intelligence has maintained a steady graph of growth in the past few years. But the pandemic led to a rapid digital transformation, which further prompted rapid innovation in the realm. As per McKinsey's State of AI survey published in November 2020, half of the survey respondents had stated their companies had adopted AI in at least one function. Experts well versed in the AI domain predict that it'll continue to experience vast expansion and development in meaningful ways in 2021 and beyond. Let's mull over some of the developments in the domain of AI that you can expect.

As AI becomes more ubiquitous, it's also become more autonomous -- able to act on its own without human supervision. This demonstrates progress, but it also introduces concerns around control over AI. The AI Arms Race has driven organizations everywhere to deliver the most sophisticated algorithms around, but this can come at a price, ignoring cultural and ethical values that are critical to responsible AI. Though regulation hasn't reached a boiling point yet, AI governance will continue to be a hot topic in 2021. As AI becomes more pervasive, more and more stakeholders are waking up to the potential problems it introduces for the public.

The arrival of the New Year brings us to think in many areas. What does 2021 hold in store for artificial intelligence? Here are 10 Artificial Intelligence predictions, from academic research to capital markets to regulation. We will take stock in December 2021 to assess the results. Autonomous vehicle developers like Waymo and Cruise have ongoing and massive cash flow needs.

Artificial intelligence has become widely deployed across several industries. Of course, bad news always gets preference and catches people's minds. Some of the popular bad news in AI have been related to fake news generation, autonomous vehicles killing pedestrians, AI systems attacking a production facility and data biases creating problems in AI applications. Nonetheless, there are still some positive signs, we have seen innovative devices being deployed in hospitals, AI tools helping disabled people, robots being used in increasing set of domains as well as AI assistants and smart devices guiding people in day to day queries and chores. The speed of evolution, adoption, and research in artificial intelligence is accelerating.

Artificial intelligence has become widely deployed across several industries. Of course, bad news always gets preference and catches people's minds. Some of the popular bad news in AI have been related to fake news generation, autonomous vehicles killing pedestrians, AI systems attacking a production facility and data biases creating problems in AI applications. Nonetheless, there are still some positive signs, we have seen innovative devices being deployed in hospitals, AI tools helping disabled people, robots being used in increasing set of domains as well as AI assistants and smart devices guiding people in day to day queries and chores. The speed of evolution, adoption, and research in artificial intelligence is accelerating.

Artificial intelligence (AI) has become integral to practically every segment of the technology industry. AI is even being used to improve AI. What changes in core AI uses, tools, techniques, platforms, and standards are in store for the coming year? Here is what we're already starting to see in 2020. AI hardware accelerators have become a principal competitive battlefront in high tech.

Artificial intelligence (AI) has become integral to practically every segment of the technology industry. AI is even being used to improve AI. What changes in core AI uses, tools, techniques, platforms, and standards are in store for the coming year?