In this week’s roundup, learn about how understanding the brain informs artificial intelligence (AI), how the technology is industrializing, and how AI-assisted drug discovery is receiving the most investment dollars. Also, get a list of the top YouTube channels for data science and find out five use cases where machine learning (ML) can make a big difference in businesses.
By Matthew Mayo, contributor for KDNuggets.com
Looking for good data science channels on YouTube? Look no further. This is a qualitative approach to identifying the highest value channels. They looked at a few key pieces of data: number of subscribers, total views by channel, number of views per subscriber, and keywords. There’s also a visualization of the data to provide an overview of the findings.
By Will Douglas Heaven, contributing writer for TechnologyReview.com
Jeff Hawkins has been straddling the worlds of neuroscience and technology for 40 years. Today, he runs a neuroscience research company. Initially, his team studied the neocortex, the part of the brain responsible for identifying intelligence. He and his team have shifted focus from brains to AI, applying what they’ve learned about biological intelligence to machinery. This article is an interview with Hawkins about what his research means for machine intelligence.
by Brian Walsh, contributing writer for Axios.com
The Stanford Institute for Human-Centered Artificial Intelligence (HAI) released its annual AI Index last week. The biggest takeaway from the report is that AI is becoming its own, true industry. AI is present in nearly every area of business, but challenges around ethics and diversity grow alongside these advancements in technology. This article highlights newly reported key points, findings, and takeaways both positive and negative as AI continues to mature.
Money is Pouring in to A.I.-Assisted Drug Discovery, While Fewer A.I. Startups Are Getting VC Backing
By Jeremy Kahn, contributing writer for Fortune.com
Bringing the power of machine learning to drug discovery has been a priority this past year accelerated by the pandemic. This can be proven by looking at the number of investments to companies and projects in this area. Although startups received a record amount of funding last year, a much smaller amount of companies were actually given funding compared to previous years. What does this mean for the technology? Find out here.
By Vyacheslav Gorlov, contributing writer for ArtificialIntelligence-News.com
The collective approach to running business has drastically shifted due to the pandemic, with many positions transitioning to remote work. This has revealed areas where the traditional approach to managing business is creating waste. ML can potentially help clean these processes up. Here are five specific cases where ML could make a big difference.
Did you see an interesting article in the last week? Share it with us! Send it to astuttle [at] lityx.com.