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Tesla Negotiating With Samsung To Produce Next-Gen Full Self-Driving Chip: Reports

International Business Times

A joint project between Tesla and Samsung, which aims to create a full self-driving (FSD) chip is currently under negotiation, according to reports. The said chip, which will be produced by the South Korean electronics giant and designed by the American electric vehicle company as per Electrek, will power Tesla's next computer, dubbed Hardware 3. This computer will be able to deliver full self-driving capacity through future software updates. In a statement at Tesla AI Day, CEO and product architect Elon Musk expressed his confidence that the computer will be able to attain full self-driving. "I am confident that Hardware 3, or the Full Self-Driving computer 1, will be able to full self-driving at a safety level much greater than humans. I don't know, probably 200 or 300% better than a human," Musk said.

Who is responsible if a self-driving car kills a pedestrian to save the driver?


Here's a scary thought: as the march of the robots continues globally, and as artificial intelligence increasingly displaces human will, your last line of defence is the men and women of Dáil Éireann. No slight intended on our current crop of TDs, but politicians globally are ill-prepared to address what is probably the most immediate existential threat to humanity outside of climate change and nuclear war.

Arabesque Introduces Autonomous Asset Management - OpenBusinessCouncil Directory


Arabesque has unveiled its Autonomous Asset Management offering for the creation of highly customised and sustainable active investment strategies, powered by an artificial intelligence technology that can generate and operate millions of active equity strategies. Developed by Arabesque AI, 'AutoCIO' enables asset managers and investment professionals to configure and build hyper-customised active strategies that can be tailored to each investor through more than a thousand different personalised investment options. The launch comes as the asset management industry increasingly looks to leverage technologies like automation and AI for cost-efficient product development, alpha generation and delivering a customised and differentiated client experience. With over USD 400 million currently powered by Arabesque's AutoCIO, the platform offers investors an unprecedented degree of customisation through a streamlined web app that can generate a vast range of bespoke strategies, with AI used to forecast stock performance across 25,000 equities daily. Speaking about today's announcement, Georg Kell, Chairman of the Arabesque Group, said: "Artificial intelligence will play a pivotal role in the customisation of active investing in the coming years, with pressure growing to innovate both in terms of technology and client centricity. "Whilst the market is increasingly demanding sustainable products that align with the objectives and values of investors, asset managers are currently unable to offer customisable, active solutions at scale.

Tesla AI Day 2021 Review -- Part 2: Training Data. How Does a Car Learn?


When people first get into contact with artificial intelligence, they tend to focus on algorithms. How they recognize pictures of cats and dogs, learn to play chess, or compose music and write poetry amaze people because it feels like magic. There are many kinds of algorithms, but most newsworthy milestones are generated by just one type -- that the media loves so much -- neural networks. People care about what deep neural networks are capable of, but they forget these "black-box" models are nothing more than empty casings without the large datasets that train them into becoming powerful predictors and classifiers. Practice makes perfect and it's no different for deep neural nets.

The things we (ought to) learn…


Yester night my drum tutor taught me a new drum-roll. Just having to grasp that new technique sparked within me an introspective tangent, as usually is the case. For close to one and a half years' now, he has been patiently taking me through the plenty foundations and a few advanced techniques in drumming. All thanks to him, I have seen how I have progressed from a wannabe drummer to at least a basic one. For me, that continual process has been in many regards, nothing short of revelatory.

Data Scientists vs Machine Learning Scientists: Career Differences


Whether you're just starting out in the workforce, have lately been laid off, is concerned about retaining your present job, or have been momentarily furloughed and have some spare time, there's no better opportunity than now to learn some AI-related skills. Machine learning and AI employment have risen 74% over the last four years, according to LinkedIn. Data scientists and machine learning scientists are among the job titles in this area, but you're not alone in being puzzled about the distinctions between the two. The in-depth examination of enormous amounts of data housed in a company's or organization's archive is what data science is all about. This study includes understanding where the data originates from, assessing its quality, and identifying if the data will be used to assist future corporate development.

The limitations of limited context for constituency parsing


Compare the above two sentences "I drink coffee with milk" and "I drink coffee with friends". They only differ at their very last words, but their parses differ at earlier places, too. Now imagine you read sentences like these. This might be a daunting task when the sentences get longer and their structures more complex. In our work, we show that this task is also difficult for some leading machine learning models for parsing.

Amazon is reportedly planning a wall-mounted Echo with a 15-inch display


Amazon is working on a number of new devices including an Echo with a 15-inch wall-mounted display, a soundbar, new Echo Auto technology and wearables. Some may appear fairly soon at the company's September 28th hardware event, according to a Bloomberg report. The splashiest-looking product would be an Alexa-enabled Echo with a display size around 15-inches. Codenamed Hoya, it could not only be placed on a stand like a regular Echo device, but mounted on a wall as well. It would serve as a smart-home center to control lights, cameras, locks and other devices, while showing weather, timers, appointments, photos and more.

Using Azure Machine Learning from GitHub Actions


Azure Machine Learning is an Enterprise-grade Machine Learning service that can help you build and deploy your predictive models faster. It also has a number of features to help you mature your machine learning process with MLOps. One of the important steps a data science team should take when starting down an MLOps path is to put all their code in source control. This allows the team to collaborate effectively and enables continuous integration in much the same way as we see for traditional software development. When any of the training code changes, we can automatically merge it with the rest of the team's changes, check the quality, and even automate training a new model.