Can data save the world. Being smart in the AI age. Bosch’s $1.1B bet on self-driving tech. https://cognitionx.com/news-briefing/.
CogX is underway and it is off to an amazing start! We have already seen over 700 knowledge-thirsty people come through The Brewery’s doors seeking to understand the impact of AI on industry, society, and government. Check out the live stream on our Facebook page and our Twitter feed for conference coverage.
Microsoft is rethinking its strategy when it comes to startup acceleration in Paris. The company is going to focus on artificial intelligence. This will lead to a new program for AI startups at Station F.
Microsoft has had a startup accelerator in the Sentier neighborhood for a few years now. When Station F opens at the end of June, the company is going to focus exclusively on artificial intelligence with a partnership with INRIA and move everything to the startup campus.
“We have to make them more productive through automation, through tools. So I’m convinced that there is in fact going to be a jobs shortage. There is going to be jobs that are unfulfilled, and that the way we’ll fill them is to take people plus computers, and the computers will make people smarter.” Of course, many disagree with his evaluation, arguing that automation threatens to put many out of their jobs.
Ed Hess from the Harvard Business Review says that we must rethink the way we think about intelligence in the age of AI. He argues that what is needed is a new definition of being smart, one that promotes higher levels of human thinking and emotional engagement. The new smart will be determined not by what or how you know but by the quality of your thinking, listening, relating, collaborating, and learning.
he says that the new smart will be about trying to overcome the two big inhibitors of critical thinking and team collaboration: our ego and our fears. Doing so will make it easier to perceive reality as it is, rather than as we wish it to be. In short, we will embrace humility. That is how we humans will add value in a world of smart technology.
Auto supplier Robert Bosch GmbH will build a 1 billion-euro ($1.1 billion) semiconductor plant, the biggest single investment in its history, as the maker of brakes and engines prepares for a surge in demand for components used in self-driving vehicles.
The factory in Dresden, Germany will start producing chips needed for autonomous vehicles, smart homes and Internet-linked city infrastructure in 2021, the world’s biggest car-parts supplier said Monday in a statement. The chips made in Dresden will be added to diverse Bosch products including airbag sensors, autonomous steering, pressure gauges and communication technologies, a spokesman said.
One particular gem from Steven Levitt: “Many of the tech companies, the new companies, do an amazing job with data. King Games [which he consulted for] was an amazing data-driven company. I honestly, though, have never seen an old firm, like a brick-and-mortar firm, that did much good with data, ever. I don’t know whether that’s a legacy of the way they think. It’s often a legacy of the systems they use. But I think the future belongs to
firms that know how to use data. The power of data in profit maximization is just incredible. If you can get people and pride and the need for power and expertise out of the way, the data can be unbelievable.”
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and compare the results.
Yesterday, Google released Tensor2Tensor
(T2T), an open-source system for training deep learning models in TensorFlow. T2T facilitates the creation of state-of-the art models for a wide variety of ML applications, such as translation, parsing, image captioning and more, enabling the exploration of various ideas much faster than previously possible.