On Tuesday, an Uber driverless car waits in traffic during a test drive in San Francisco. The ride-hailing company is refusing to obey demands by the state's Department of Motor Vehicles that it stop picking up San Francisco passengers in specially equipped Volvo SUVs. On Tuesday, an Uber driverless car waits in traffic during a test drive in San Francisco. The ride-hailing company is refusing to obey demands by the state's Department of Motor Vehicles that it stop picking up San Francisco passengers in specially equipped Volvo SUVs. Regulating Self-Driving Cars For Safety Even Before They're Built Uber has started offering rides in self-driving cars in San Francisco without a permit for autonomous vehicles -- defying state regulators, who say the permit is mandatory.

Jerry Kaplan is widely known as an Artificial Intelligence expert, technical innovator, serial entrepreneur, and bestselling author. He is currently a Fellow at The Center for Legal Informatics at Stanford University and a visiting lecturer in the computer science department, where he teaches social and economic impact of Artificial Intelligence. Kaplan founded several technology companies over his 35-year career, two of which became public companies. As an inventor and entrepreneur, he was a key contributor to the creation of numerous familiar technologies including tablet computers, smart phones, online auctions, and social computer games. Kaplan is the author of three books: the best-selling classic Startup: A Silicon Valley Adventure; Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence (2015); and Artificial Intelligence: What Everyone Needs to Know (2016). In 1998, Kaplan received the Ernst & Young Emerging Entrepreneur of the Year Award, Northern California. He has been profiled in The New York Times, The Wall Street Journal and Forbes, among others. He received a BA degree from the University of Chicago and a PhD in Computer and Information Science from the University of Pennsylvania. Jerry will be speaking at the Gigaom AI Now in San Francisco, February 15-16th.

Here are some story lines I don't want you to miss today. Donald Trump has chosen one of the most consistently conservative presidential cabinets in recent history -- one whose presumed members' views don't always align with what Trump promised on the campaign trail. In Washington circles, the biggest guessing game is how it will all play out. Somehow, you have to think tweeting is involved. We don't want to jinx it, but … all of California should be in for some rain today.

What started with a Siri-like chatbot to provide localized refugee information led to various UN agencies backing the idea of a hackathon to develop tech to help in Syria's humanitarian crisis. By February this year, Lebanon was hosting about 1.1 million refugees from neighboring Syria, which amounted to about one in five people in the country, according to Amnesty International. Since then the numbers have continued to grow. Alongside those figures, 4.8 million Syrian refugees are registered with UNHCR in Egypt, Iraq, Jordan, Lebanon, and Turkey. With Syria's civil war and the resulting humanitarian crisis showing no signs of abating, one Lebanon-based US entrepreneur, Mike Clarke, director of The Humanitarian Innovation Lab, is working with agencies like UNHCR, UNICEF, and OCHA "to inspire and cultivate new technologies that can quickly improve the current response to the refugee crisis in Lebanon".

I've written before about the apparent shift in healthcare whereby making sense of the vast quantities of data produced within the system is key to successful treatment of patients. Nowhere is this moreso than in cancer care. For instance, a team from UCL utilized deep learning earlier this year to more accurately identify cancer cells. This trend is continued with a second study, which aims to make sense of the cancer data currently sitting in the cancer registry program that's coordinated by the National Cancer Institute (NCI) and the Centers for Disease Control and Prevention. This database has records of cancer incidences across the US, but the curation of it can often be a hugely time-intensive process as it requires manual editing and annotation from experts for each file.

A few days ago I found out that there had appeared lda2vec (by Chris Moody) – a hybrid algorithm combining best ideas from well-known LDA (Latent Dirichlet Allocation) topic modeling algorithm and from a bit less well-known tool for language modeling named word2vec. And now I'm going to tell you a tale about lda2vec and my attempts to try it and compare with simple LDA implementation (I used gensim package for this). What is cool about it? It means that LDA is able to create document (and topic) representations that are not so flexible but mostly interpretable to humans. Also, LDA treats a set of documents as a set of documents, whereas word2vec works with a set of documents as with a very long text string.

Britain's fertility regulator is meeting to decide whether or not to allow so-called'three-parent baby' treatments for inherited diseases (stock image used) Mexican clinic plans 20 three-parent babies in 2017:... Crop spray makes wheat 20% larger... and it's GM free!... The robotic arm you can control with your MIND: Researchers... Thinking with your hands can boost creativity: Children who... Mexican clinic plans 20 three-parent babies in 2017:... Crop spray makes wheat 20% larger... and it's GM free!... The robotic arm you can control with your MIND: Researchers... Thinking with your hands can boost creativity: Children who... A fertility clinic in Mexico which helped a couple to conceive the world's first'three-parent baby' says it plans to conceive a further 20 babies using the technique in the first half of 2017 (stock image used) WHY IS THE METHOD CONTROVERSIAL? Dr John Zhang, head of the New York City embryonic team, holds the world's first'three-person' baby after the boy was born in Mexico in April.

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Safeguarding the data is at the heart of security, more critical than protecting the network or perimeter. CIOs need to pick up where traditional security tools end and investigate AI cybersecurity digital safety nets.

Self-driving-cars are notoriously difficult to test for safety. Hotz writes in an email, "It's not my code, I did not release it"--Comma.ai Inc. "released and maintains it." Most legal experts that spoke with IEEE Spectrum--and Hotz himself--believe that if you use the company's code and something goes wrong, then it isn't liable for damages. But Consumer Watchdog advocate John Simpson doesn't believe this is fair.