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HOT TOPICS
- The Accelerator Conundrum
- The Startup Velocity Question
- Platform as a Service
- Man and Superman
- Web 3.0 = (4C + P + VS)
- The Future: End of Capitalism
- Capitalism 2.0
1Mby1M Virtual Accelerator Investor Forum: With Ankit Jain of Gradient Ventures (Part 3)
Sramana Mitra: I was talking to a friend at a party last weekend. He’s very experienced and successful serial entrepreneur. He has invested in an AI company that is doing very well. But this question of hiring AI talent is very serious right now. Let me ask you the geography question. What is your footprint?
1Mby1M Virtual Accelerator Investor Forum: With Ankit Jain of Gradient Ventures (Part 2)
Sramana Mitra: Double-click down for me on your definition of early stage. You said check size is from $1 million to $10 million. What is your definition of early stage? What does an AI startup need to show to be able to convince you that is has enough validation that there is something there? Ankit
1Mby1M Virtual Accelerator Investor Forum: With Ankit Jain of Gradient Ventures (Part 1)
Responding to a popular request, we are now sharing transcripts of our investor podcast interviews in this new series. The following interview with Ankit Jain was recorded in May 2018. Ankit Jain is Founding Partner at Gradient Ventures, Google’s AI venture fund. Sramana Mitra: Let’s introduce you to our audience. Tell us about yourself a
Thought Leaders in Artificial Intelligence: Steve Scott, CTO of Cray (Part 5)
Sramana Mitra: Do you have any thoughts on this problem that is being discussed nowadays? AI is a bit of a black box and all these biases that are creeping into AI are going to drive society in the next several decades. We don’t really have a very good understanding of what really the AI
Thought Leaders in Artificial Intelligence: Steve Scott, CTO of Cray (Part 4)
Steve Scott: With the advent of GPU computing, deep neural nets started to become enabled to the point where you could get good enough performance so that you could really do useful things with them. GPU computing is the application of the processors that were designed for highly parallel tasks of painting triangles on the
Thought Leaders in Artificial Intelligence: Steve Scott, CTO of Cray (Part 3)
Sramana Mitra: Can you give an example? Steve Scott: If you think about deep neural networks in particular, there’s training and there’s inference. Training is the learning part where you take a bunch of data and based on that, you train a model to be able to provide some function. Inference, of course, is using
Thought Leaders in Artificial Intelligence: Steve Scott, CTO of Cray (Part 2)
Steve Scott: The way people have used Cray and other high-performance supercomputers is, you have a bunch of equations that present a model for the natural world whether that’s equation of airflow across an airplane wing or equations dictating the molecular dynamics involved in drug discovery. You iteratively solve these equations spread across these points
Thought Leaders in Artificial Intelligence: Steve Scott, CTO of Cray (Part 1)
Steve takes us deep into the field of high performance computing and how AI is impacting it. Sramana Mitra: Let’s start by having you introduce yourself a little bit as well as Cray’s activities in the domain of AI currently. Steve Scott: I’m the Chief Technology Officer at Cray. I’ve been with Cray most of
