Sergii Shelpuk @sshelpuk
Co-founder & CEO @ https://t.co/OnsOtnYlos. AI consultant @ https://t.co/DbzyCAMJ8P shelpuk.com Joined September 2015-
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📢 Check out my latest blog post on building sustainable competitive advantages with tech and #AI products! 🚀 Discover the power of network effects and how they propel companies like #Apple, #Microsoft, and #Meta to unparalleled success. shelpuk.com/post/all-you-n…
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Looking to build a sustainable #AI competitive advantage? Avoid these common mistakes in your AI strategy. Check out my latest blog post to learn more: shelpuk.com/post/building-… #MachineLearning #DataScience
Ok, Twitter, how do I ban all posts mentioning "GPT" here? The "AI influencer" crowd grew absolutely unbearable over the last months.
@prittjam @ducha_aiki It was an epic journey :) I'm good, currently in Warsaw. Ping me if you are around.
@prittjam You were right, it's Glagolitic. There's even a Wikipedia article on that (Ukrainian only, though): uk.m.wikipedia.org/wiki/%D0%93%D1…
Sergii Shelpuk retweeted
My unwavering opinion on current (auto-regressive) LLMs 1. They are useful as writing aids. 2. They are "reactive" & don't plan nor reason. 3. They make stuff up or retrieve stuff approximately. 4. That can be mitigated but not fixed by human feedback. 5. Better systems will come
Sergii Shelpuk retweeted
найвища честь для автора – читач
Even after a decade of hand-on, ML keeps amazing me with its unpredictability. I still cannot be sure whether certain model, feature set or label design outperforms the alternative. Experimentation remains the best modus operandi.
@srchvrs They are also perfectly compatible. I personally developed an ML system for genomic data that used ProcessPoolExecutor for data processing AND ThreadPoolExecutor for multi-model training within the same experiment.
@srchvrs Right, they don't. If you need shared data access and do not mind the global interpreter lock, use ThreadPoolExecutor. Example: training N models on N GPUs. If you do not need shared data access, use ProcessPoolExecutor. Example: data processing on the CPU side.
@TimothyDSnyder In Ukraine, every oligarch has his own media company. These companies loose money for decades, but remain active. Their purpose is to influence masses, not to make money. If one's businesses depend on a particular social media platform, it makes perfect sense to acquire it.
6/6 Despite speculative statements about the possible benefit of the model for humanity in the future, its destructive effect is available on the spot to anyone willing to pay 2 cents per 1000 words - automatic propaganda, hatred, and destruction of factuality as such.
5/6 Thus, GPT-3 and ChatGPT are a “dead end” from AI as a competitive advantage point of view. If a co-pilot niche market for software development does emerge in the future, it will use smaller and much cheaper-to-train models.
1/6 GPT-3 model that lies in the heart of ChatGPT is gigantic. It has 175B weights and requires 800 Gb for storage. Its training cost is estimated to be $4M+. This makes it impossible to train the model from scratch for all but a few potential users. bit.ly/3uIIxRv
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