ergey A. Razin has joined SIOS in September 2012 and responsible for driving SIOS’ strategy, and innovation. In addition Sergey is a co-founder and currently serves as a member of the planning committee for Palmetto Open Source Conference (http://www.posscon.org) as well as active contributor to a number of open source initiatives. Prior to joining SIOS Sergey was an architect for EMC Unified Storage division and EMC CTO office where he drove number of initiatives in areas of network protocols, cloud and storage management, metrics, and analytics as well as innovation. Throughout his academic and professional career Sergey served roles of Principal Investigator (PI), leader in research, development as well as architecture in areas of big data analytics, speech recognition, telephony, and networking. Sergey holds PhD in computer science from the Moscow State Scientific Center of Informatics, where he researched Natural Language Processing (NLP) and media processing. He also holds BS in Computer Science from the University of South Carolina.
Open AI is working on a very important initiative in realm of Artificial General Intelligence (AGI) that spans both technology as well as an attempt to look at the regulations, transparency and other aspects of what would be required to get AIG “loose”.
In addition to that, Open AI has also released a portion of their work in realm of natural language GPT2 model (https://openai.com/blog/better-language-models/). This model was trained on OUR public internet “playground” with all corresponding issues, biases, and things that we hate and love (more hate) about our digital world. However, only portion of the model has been release with the message, that if “we” (them) would have released the entire “thing”, it will cause chaos and destruction (exaggerating of course). While I do appreciate the thought, eventually it will come out.
How does AGI look like today? What can you do with it? That’s what we will attempt to answer further in this post.
Recently I have visited one of the probably the best data (data not Machine Learning or AI) conferences called Conf2017 by Splunk.
Why was is the best data conference?
A lot of data conferences these days are very high-level while this one is very technology oriented that bring corresponding crowd. Conversations are very interesting, attendees are very interested, curious, exploring and quite intelligent, which is always interesting to engage with an intelligent people.
Been working on a very interesting initiative in space of Machine Learning analytics but now trying to get back in groove of things and continue exploring some of the emerging technologies, ask hard question, and see how we (as a community of technologies) see the world evolving as we going through all kinds of transformations that are pushed both by business initiatives as well as technologies.
Let’s begin our conversation on the topic of time warps and self-learning behavioral models.
Finally, looks like the “knobs war” is coming to its logical conclusion. In the past 5 years there was a huge hit on the knobs, and by knobs I mean APIs (interfaces) that being exposed by different virtulization/cloud platforms. The “hit” was in particular centered around providing a layer on the top (the MASTER knob) that would provide ability to manipulate through a higher level interface (aggregated/federated knob) the knobs underneath. But with that the announcement of the AWS Management Portal for vCenter it becomes clear that this place is now closed.
Or should I say Ceph in the RedHat ;) I have been working hard on all kinds of interesting and innovative things that I will start sharing on soon, but this one worth discussing first. In my last post SAN vs OpenSource I was discussing the benefits of open source Software Defined Storage (SDS) initiative comparing it to SAN looking at two through the lens of Ceph. Another interesting post that was quite popular (according to the Google Analytics) is Ceph vs Gluster who interesting enough now joined under the RedHat or have they?