AWS Data Exchange vs Data Banks – part 2
Saw where AWS announced a new Data Exchange service on their AWS Pi day 2023. This is a completely managed service available on the AWS market place to monetize data. In a prior post on a topic I called data banks (Data banks, data deposits & data withdrawals…), I talked about the need to have…
Keep readingLLM exhibits Theory of Mind
Ran across an interesting article today (thank you John Grant/MLOps.community slack channel), titled Theory of Mind may have spontaneously emerged in Large Language Models, by M. Kosinski from Stanford. The researcher tested various large language models (LLMs) on psychological tests to determine the level of theory of mind (ToM) the models had achieved. Earlier versions…
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Data and code versioning For MLops
Read an interesting article (Ex-Apple engineers raise … data storage startup) and research paper (Git is for data) about a of group of ML engineers from Apple forming a new “data storage” startup targeted at MLOps teams just like Apple. It turns out that MLops has some very unique data requirements that go way beyond…
Keep readingNVIDIA H100 vs. A100 GPUs in MLPERF Training
NVIDIA recently released some “Preview” results for MLPerf Data Center Training v2.1 (most recent results as of 28 Nov 2022) benchmarks. We analyzed these results to determine how much faster the H100 was vs. their A100 GPU. Note, NVIDIA submitted 3 series of Preview benchmarks using the H10-SXM5-80GB GPUs for training which included an 8…
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FAST(HARD) or Slow(soft)AGI takeoff – AGI Part 6
I was listening to a podcast a couple of weeks back and the person being interviewed made a comment that he didn’t believe that AGI would have a fast (hard) take off rather it would be slow (soft). Here’s the podcast John Carmack interviewed by Lex Fridman). Hard vs. soft takeoff A hard (fast) takeoff…
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The Hollowing out of enterprise IT
We had a relatively long discussion yesterday, amongst a bunch of independent analysts and one topic that came up was my thesis that enterprise IT is being hollowed out by two forces pulling in opposite directions on their apps. Those forces are the cloud and the edge. Cloud sirens The siren call of the cloud…
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Deepmind does chat
Read an article this week on Deepmind’s latest research into developing a chat agent (Improving alignment of dialogue agents via targeted human judgements). Lot’s of interesting approaches have been applied to chat but even today, most chat model’s are rife with problems, that include being bigoted, profane, incorrect, etc. Reinforcement learning vs. deep neural networks…
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NVIDIA’s H100 vs A100, the good and bad news
Turns out only the current MLPerf v2.1 Data Center Inferencing results show both NVIDIA Hopper H100 and prior generation NVIDIA A100 GPUs on similar workloads so that we can compare performance. Hopper (H100) results are listed as CATEGORY: Preview, so final results may vary from these numbers (but, we believe, not by much). For the…
Keep readingMTJ’s everywhere
We have been requested to remove this post by the lecturer who supplied the information discussed in this post. We are complying with this request as of 05 October 2022. The Editors
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