Artificial intelligence grew by leaps and bounds over the years, leaving its footprint across different sectors, including marketing, healthcare, telecommunication, human resource, government, banking and what have you. The big companies are always on the lookout for new ways to upgrade their workflows. To that end, companies like Apple, Microsoft, Google and Facebook have embraced AI with open arms. Unlimited resources, budget, and market position allow big companies to drive innovations at warp speed. In contrast, small companies find AI beyond their paygrade.

A 2020 report by Frost & Sullivan stated that 90% of industrial enterprises will be utilising edge computing by 2022. The value of the data that can be gleaned from intelligence ‘in the field’ is clear, but the current limitations of low power, on-device compute, data management and processing across the edge computing landscape continue to pose multiple engineering challenges. We’re thrilled to announce the agenda for the 3rd annual Edge AI Summit, which was the first ever dedicated summit focused on deploying machine learning on devices, and on the network infrastructure that supports the intelligent IoT. This year is all about Edge AI case studies! From ultra-low-power microwatt applications at the ‘sensor edge’, to larger milliwatt examples at the ‘device edge’ up to the non-power constrained ‘server-network edge’; we’ll be gathering a global audience (virtually!) to explore the most innovative real-world use cases of hardware and software facilitating AI at the Edge with examples from Uber AI, Google, Bosch, Magic Leap, Rakuten and many more…

The rest of the thread, Tell me about a paper that you found inspiring, from u/mitare is also quite interesting. This paper is a really comprehensive review detailing what exactly current ML techniques are unable to do that humans can do very well. It lays the groundwork that needs to be done to make human-level artificial intelligence.

Zoubin Ghahramani is Chief Scientist of Uber and a world leader in the field of machine learning, significantly advancing the state-of-the-art in algorithms that can learn from data. He is known in particular for fundamental contributions to probabilistic modeling and Bayesian approaches to machine learning systems and AI. Zoubin also maintains his roles as Professor of Information Engineering at the University of Cambridge and Deputy Director of the Leverhulme Centre for the Future of Intelligence. He was one of the founding directors of the Alan Turing Institute (the UK's national institute for Data Science and AI), and is a Fellow of St John's College Cambridge and of the Royal Society.

Uber is a driving application from which you can request a car directly to your door. From the application, you can see where your driver is, the time it will take for them to arrive, how many stars the driver has and so much more. The app has become widely-used around the world because of its convenience and low prices. Uber hasn't kept it a secret. They want to be the first ones on the market with self-driving cars.