As my family can attest, admitting when I am wrong has never been easy for me; but I feel it is important that I share a recent, if rather late, realization I had. Before attending the Techonomy Climate event in March, I didn't fully understand the scope and importance of the climate crisis. I am sharing my experience and perspective in the hopes that I may inspire some of my like-minded peers to grasp not only the urgency of this issue but also the tremendous business opportunities it holds. Like many of my friends and colleagues, my sense of purpose has always lain with the protection and prosperity of my family, friends and employees. I think this worldview is both natural and understandable.

Weighted voting games apply to a wide variety of multi-agent settings. They enable the formalization of power indices which quantify the coalitional power of players. We take a novel approach to the study of the power of big vs. small players in these games. We model small (big) players as having single (multiple) votes. The aggregate relative power of big players is measured w.r.t. their votes proportion. For this ratio, we show small constant worst-case bounds for the Shapley-Shubik and the Deegan-Packel indices. In sharp contrast, this ratio is unbounded for the Banzhaf index. As an application, we define a false-name strategic normal form game where each big player may split its votes between false identities, and study its various properties. Together, our results provide foundations for the implications of players’ size, modeled as their ability to split, on their relative power.

News broke this week that Woven Planet, a Toyota subsidiary, will acquire Level 5, Lyft's self-driving unit, for $550 million. The transaction, which is expected to close in Q3 2021, includes $200 million paid upfront and $350 million over a five-year period. Toyota will gain full control of Lyft's technology and its team of 300. Lyft will remain in the game as a partner to Toyota's self-driving efforts, providing its ride-hailing service as a platform to commercialize the technology when it comes to fruition. The Toyota-Lyft deal is significant because it comes on the back of a year of major shifts in the self-driving car industry.

Andy is one of the most influential minds in data science with a CV to match. He shares his thoughts on distributed machine learning with open-source tools like Dask-ML as well as proprietary tools from the big cloud providers. In a past post, we covered distributed ML use cases and discussed whether or not we really need distributed machine learning. You can check it out here. This interview was lightly edited for clarity.

With the COVID-19 pandemic outbreak, businesses are at a halt, and that has created a significant impact on the artificial intelligence-based startups, who are continuously struggling to stay afloat amid this downturn. In fact, a recent report has confirmed that 90% of tech startups, including the ones working with artificial intelligence and machine learning, in the country, are facing a significant decline in revenues due to the impact of COVID-19 pandemic. And approximately 30-40% of those startups are in the process of closing down due to halted operations and having no financial back up to continue the business. This pandemic has injured the backbone of the economy, which, in turn, poses a lot of dilemmas for investors to finance businesses amid this crisis. Venture capitalists have already warned startups about the difficult times ahead.

The world of genomics has made abrupt strides in the past several years, with the first CRISPR-edited babies being born just a few weeks ago. Using advanced CRISPR technology, Scientist Jiankui He'announced that twin girls with an edited gene that reduces the risk of contracting HIV "came crying into this world as healthy as any other babies a few weeks ago."' The announcement was met with great backlash, sparking'outrage from many researchers and ethicists who say implanting edited embryos to create babies is premature and exposes the children to unnecessary health risks. Opponents also fear the creation of "designer babies," children edited to enhance their intelligence, athleticism or other traits.' CRISPR technology is used in editing human genomes.

This article is a continuation of'Machine learning is getting BIG (Part I)' previously published on this blog. As well as cost in terms of dollars, people have started calculating the cost of training these huge models in terms of greenhouse gas emissions. When neural architecture search was included, training a single'transformer' model was found to generate more carbon dioxide than 4 lifetimes of car use. It is true that modern hardware is much more efficient than older hardware. Although the improvement in efficiency has not tracked the increase in use of energy on these projects. Those are the run time costs.

Artificial intelligence (AI) is influencing almost every facet of our lives. It is transforming the way we live, work and communicate. Whether it is professional front or personal, AI is becoming a part of everything now. It is revolutionizing the manufacturing and business processes for organizations and improving our homes and cities. AI applications and analytics use data science and algorithms for automation and optimization of processes.

Artificial intelligence (AI) is one of those technologies that excites the public and business imagination alike. Long since a favourite theme in science-fiction, it is now gaining traction in everyday practical scenarios. In 2018, we saw a considerable rise in the adoption of AI around the world and across industries, with businesses using it to improve operations, generate new innovations and boost customer experience. To make artificial intelligence work for a business, leaders need to ensure that employee skills are honed in line with technological investments. With financial services, telecoms and high tech leading the way in bringing AI into the mainstream, and other areas such as automotive, healthcare, energy and retail also embracing it, we expect the rapid growth of AI to continue in 2019 as companies strive to get the most value and competitive advantage from the data they capture.

It may be a long time before you can own a truly self-driving car. But chipmakers are placing bets that you will. On Tuesday, the Japanese chipmaker Renesas, the second-largest provider of semiconductors for the automotive industry, said it will acquire San Jose based chipmaker Integrated Device Technology (IDT) for $6.7 billion, in part to prepare for autonomous vehicles. IDT has not historically provided chips for cars, but it does have sensor and wireless technologies that could help Renesas compete in the market for chips for autonomous vehicles. "Renesas and IDT have complementary technologies," says Objective Analysis analyst Jim Handy.