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Replying to @pentagoniac
Real Reasoning Requires Recurrence.
Christopher Nguyen ⽗
16.1K posts
Christopher Nguyen ⽗
@pentagoniac
CEO @Aitomatic—Builder, Leader, Professor, Advisor—Panasonic/Google/HKUST/Refugee—bit.ly/ctn-scholar. Industrial Brain Engg & Robotics—github.com/aitomatic/dana
- Replying to @pentagoniac and @calleymeansI was sufficiently curious.
- Me: What is Knowledge-First AI? GPT: Knowledge-first AI is a type of AI that focuses on using knowledge to solve problems, as opposed to other approaches that focus on learning from data.
- Set a reminder to join and listen to industry leaders and investors talk about #IndustrialAI for the $25T Industrial economy. Friday 11/11 at 7pm PST! x.com/i/spaces/1BdGY…
- GDP explains almost 70% of pessimism toward AI. But perhaps not in the direction you think. @StanfordHAI has come out with the excellent annual AI Index aiindex.stanford.edu/report/. It referenced an IPSOS Global Survey from 2022 on positive/negative expectations from AI.
- The whole clip shows @karaswisher being intellectually honest about Elon, seeing all the good, bad, and ugly. And that Bill Maher agrees with her assessments. Is that not better than to be a simpleton fanboy/hater?Can anyone explain to me why anyone should care what Kara Swisher thinks about anything?
- “This week on TheDataExchangePod: @pentagoniac, CEO @aitomatic. We discuss the unique challenges and opportunities in combining human & machine intelligence.” HT @bigdata.
- Replying to @DavidSacksThey can absolutely both be true, or rather, best estimates. This is because the numbers come from entirely different sets (see Venn diagram below): (A) company payrolls (“Establishment”, YELLOW), which does not include a whole lot of jobs that *are* included in (B) individual
- People underappreciate what you mean by cat-telligence esp. for Planning & Reasoning, @ylecun. (Via tiktok.com/@crabfren/vide…)
00:00 - Replying to @NaveenGRaoBy this measure, search was not “free” either, Naveen. Google did benefit quite a bit from the ’00 crash with capex, and “cheated” for a while with power until one of our racks burned down a colo 😎. And you’re right that a profitable business model took time to find—long-tail
- 12 years ago, a colleague from SRI (“Siri”) & I struggled for months—to build a pipeline of audio codecs, speech & language models out of bi-grams—to build a marginally acceptable ASR for a mobile-butler app. Today something 100x better can be done in dozens of lines of code.New tutorial on keras.io: build an automatic speech recognition system using a CTC loss and a model inspired by DeepSpeech2. End-to-end (from raw wave files to inference with the trained model) in... *200 lines of code** 🤯keras.io/examples/audio…
