In an interview with Mathias Döpfner, the CEO of Axel Springer, Business Insider's parent company, Elon Musk revealed his thoughts on self-driving cars, oversight of artificial intelligence, and reasons behind his quest to be buried on Mars. Musk, who had announced in October Tesla's release of a beta version of its long-awaited "full self-driving" software, clarified that he is "definitely not trying to take anyone's steering wheel away from them." "I'm just saying what will most likely occur, and I am certain about this, is that self-driving will become much safer than a human driver. Probably by a factor of 10," he told Döpfner, adding that the bar for whether a person will be able to drive or not will be much more "stringent" in the future when autonomous driving is "10 times safer." But as Business Insider's Graham Rapier reported, the top US safety regulator, the National Highway Traffic Safety Administration, has repeated that "no vehicle available for purchase today is capable of driving itself." "The most advanced vehicle technologies available for purchase today provide driver assistance and require a fully attentive human driver at all times performing the driving task and monitoring the surrounding environment. Abusing these technologies is, at a minimum, distracted driving. Every State in the Nation holds the driver responsible for the safe operation of the vehicle," the agency said.

Katharina Volz is applying machine learning to finding and developing cures for brain-aging diseases, one of science's biggest conundrums. Born in Ulm, Germany (the birthplace of fellow scientist Albert Einstein), Volz was the first-ever Ph.D. in stem cell biology and regenerative medicine at Stanford University. Entrepreneurship did not come easily to Volz, a trained scientist. But a dogged passion for unearthing a cure for brain-aging disease is what pushed her to persevere. As the founder and CEO of OccamzRazor, a biotechnology firm, she's set out to treat a disease that hit close to home.

Gebru, an alumni of the Stanford Artificial Intelligence Laboratory, is one of the leading voices in the ethical use of artificial intelligence. She is well-known for her work on a landmark study in 2018 that showed how facial recognition software misidentified dark-skinned women as much as 35% of the time, whereas the technology worked with near precision on white men. She has also been an outspoken critic of the lack of diversity and unequal treatment of Black workers at tech companies, particularly at Alphabet Inc.'s Google, and said she believed her dismissal was meant to send a message to the rest of Google's employees not to speak up. Platformer received the email Gebru sent; she herself did not have access to her account after Google terminated her. It is published in full below.

The UK government recently published a review of algorithmic bias – an important and even crucial subject as ever more decision-making progresses from wetware to silicon. However, it would have been useful if they'd understood what Gary Becker told us all about discrimination itself – work for which he won the Nobel prize for economics. Almost all the things they are worrying about solve themselves within his logical structure. First though, a linguistic structure – let's examine the difference between algorithms and artificial intelligence (AI). An algo doesn't have to be encoded at all, it's a set of rules by which to make a decision – usually, almost always, derived from the current methods by which we make such decisions, just formalised or even coded.

Yang Liu, an Alexa AI principal scientist, and Ruhi Sarikaya, director of applied science, Alexa AI, have recently been named IEEE Fellows. The designation takes effect January 1, 2021. Liu is being honored for her "contributions to speech understanding and language-learning technology", while Sarikaya is being recognized for his "leadership in spoken language processing, and conversational understanding systems". Both currently lead research initiatives focused on making Alexa more natural and conversational, perceptive and context aware, and capable of self learning. The IEEE Fellow designation is conferred by the IEEE board of directors upon individuals with outstanding records of accomplishment in any of the IEEE fields of interest.

A 15-year-old scientist and inventor has been named as Time magazine's first "kid of the year". Gitanjali Rao, from Denver, Colorado, has invented new technologies across a range of fields, including a device that can identify lead in drinking water, and an app and Chrome extension that uses artificial intelligence to detect cyberbullying. She said she hoped she could inspire others to dream up ideas to "solve the world's problems". Gitanjali was chosen from a field of 5,000 US-based nominees, which was whittled down to five finalists by a committee of young people alongside comedian and TV presenter Trevor Noah. She and the other four finalists will be honoured in a TV special next Friday.

While'data' might be the new oil, the'dataset' is the refined gasoline that powers every Machine Learning (ML) and AI operation. These datasets are used to boost signal, accuracy, precision, profit/loss, Sortino or Sharpe ratios in the financial markets and biosciences industries. The following is a transcript of a recent AMA hosted by ABT Crypto Academy on Telegram with the founder of Vectorspace AI, Kasian Franks. We're extremely privileged to be joined by Kasian Franks the CEO of Vectorspace, it's only right we start off with a brief introduction -- can you tell us what exactly Vectorspace is and how the idea came about? We got our start in Life Sciences, now most refer to it as Biosciences at Genentech and Lawrence Berkeley National Lab https://www.lbl.gov There we were tasked with creating a system to identify hidden relationships between genes, drugs and diseases connected to breast cancer, chromosomal radiation damage and extending human lifespan for the purpose of deep space travel. We wrote a paper with Micheal I. Jordan, teacher of Andrew Ng, who developed the first AI for Google and China's Baidu. "The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made f…" Human genes are like stocks or cryptos. Our technology is based on datasets.

Artificial Intelligence (AI) is transforming the workplace in significant ways that are being used by recruiters to expand and improve their workforce. These AI applications are not about replacing human beings as much as efficiently finding the best human beings as candidates for open job positions. AI is extremely efficient in data mining to find the keywords that will be the optimal choices for advertising copy about open job positions. AI is also effective in screening potential candidates to find a match. To have job listings rank high on the search engine results page, recruiters use AI-driven keyword optimization techniques to have the best results.

Proteins are essential to life, supporting practically all its functions. They are large complex molecules made from chains of amino acids. What a protein does mostly depends on its unique 3D structure. Understanding what shapes proteins fold into is known as the'protein folding problem,' and has stood as a grand challenge in biology for the past 50 years. In a significant scientific advance, the artificial intelligence group DeepMind's latest version of the AI system AlphaFold has been detected to solve this grand challenge by the organisers of the biennial Critical Assessment of Protein Structure Prediction (CASP). This breakthrough demonstrates the impact AI can have on fundamental fields that explain and shape the world.

In the in the local market, especially if it comes to local journalism and to the event market and the first time we heard that we thought well that, that's interesting and then we I think we went on with our other projects and the second time we heard another customer telling us about the same problem, we got more and more interested in that and then we asked a lot of media companies in Germany, what they are thinking about this specific problem and if we would solve that problem would that be a high would that provide a high value, if we would develop an automated solution for this specific task. So most of of the directors and so on we spoke to.