Category: AI Platforms

With the retirement of DAWNBench, I decided to take a look at what’s next for not only the Stanford DAWN project as it reaches its midway point, but also for benchmarking the next gen infrastructure for industrialized data science.
For this week’s episode of the Futurum Tech Podcast, I was joined by my colleague and fellow analyst, Ron Westfall. We discussed what organizations need to know about the EU’s newly proposed guidelines for AI and Apple’s hit to the bottom line as a result of the coronavirus outbreak. We also covered the T-Mobile Sprint merger and what we think is ahead in the telecoms market and explored our thoughts about the role automation will play in 5G operations. Lastly, we covered news that Google is cracking down on Google Play apps that track location in the background, along with the FTC’s probe into high tech acquisitions over the course of the last decade and what that likely means (read: the headaches potentially ahead). Come on, have a listen. And if you’ve not yet subscribed, do — we cover all the tech news of the week in an easily digestible, definitely entertaining manner.
With the rise of PyTorch, TensorFlow’s dominance may be waning. While PyTorch scale advantages are tipping the scales, deployability is still TensorFlow’s strength. Here’s a look at what I think is ahead with these two for deep learning dominance.
Ericsson’s AI-powered Energy Infrastructure Operations is blueprinted to decrease OPEX and CO2 emissions for operators using AI and data analytics to improve energy efficiency and improve site availability.
New data on smart speakers show that the market is growing at a fast pace, but it is new entrants, mostly from China that are seeing the biggest growth.
Many people tend to think of AI as purely an automation technology, but that just skims the surface of what these tools and techniques can do for us.
Nvidia delivered a strong Q4 for its FY 20 breaking revenue records in pro viz and data center while beating revenue and earnings expectations.
Just about a month after acquiring Habana Labs, Intel is pivoting its AI strategy and shedding its commitment to Nervana inference and training chips.
Launchable has emerged from stealth mode to introduce its AI-driven software test automation solution. This is exciting news for the DevOps community, as key industry figures—most notably, the Jenkins CI/CD automation server’s creator—have essentially validated that AI-driven test automation is coming big time into every software development shop. In a CI/CD context, Launchable’s adaptive AI can drive automated testing of source code changes upon check-in as well as notification of development and operations personnel when the tests fail. It can ensure that developers never have to wait more than a few minutes for feedback on their latest code changes. It can also help testers to keep pace with the growing volume, velocity, and variety of code changes, so that the most relevant changes can be tested 24x7. The challenge for Launchable is how quickly the company can gain traction in the developer community before incumbent startups in this promising niche solidify their first-mover advantage. Here are thoughts on how the company should move forward so as to quickly take advantage of this opportunity.
During NRF 2020 Oracle showed a new tools called Customer Insights that can help retailers predict their best future customers. Exploring the announcement.
Apple has acquired Xnor.ai to expand the company's on device AI capabilities. What does the Xnor.ai acquisiton mean for Apple and future Apple Devices.

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