Browse Comments — Clean (de-noised)
Close reading of the corpus at each pipeline stage: raw → clean → relevant → coded.
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Impressive. Is it available for all ratios? And what is the best resolution you can get?
The guy (new grad), 👆, already figured out the answer: Stop studying software engineering to become a junior engineer. Problem solved. lol Don’t invest in any biz or career that is not viable, now and in the future. Same as : don’t chase a person/lover that does not want you back. Don’t go where you are not wanted, welcomed or appreciated. For now, don’t pay expensive tuition to study software engineering. Save yourselves from financial stress and emotional trauma. Always begin with the end in mind. Stuck as a junior SFE? Simply pivot.
Interesting
Eric Chevalier
Ian Read, Ph.D. Unfortunately, the politicians and lobbyists aren't taking the long view. Based on what we see out of them, their focus is strictly short-term and near sighted.
how is it different to any other MoE model?
Sylwester Mielniczuk well said! Professional talking heads are the worst. Puke
Lewin Wanzer yes 100 percent
Asfandyar Fakher, agreed. Check out short video about AI (Github Copilot) + Bentley STAAD.Pro application for finite element analysis applications:
Tianyu Xu 😅😅😅 so you create an "alternate" path 😉. On that note, how do you balance the camera path annotations from, say in this case, ants and objects motion?
Amanda Wu, agreed. Check out short video about AI (Github Copilot) + Bentley STAAD.Pro application for finite element analysis applications:
Mauricio J. Shibazaki Yllana, agreed. Check out short video about AI (Github Copilot) + Bentley STAAD.Pro application for finite element analysis applications:
If your a software engineer write code for AI
The value of AI isn't just finding answers faster, it's giving researchers the freedom to ask bigger questions.
AI is accelerating the creation of knowledge. The question for companies will not be how much knowledge they can generate, but how quickly they can turn it into consistent, traceable, and executable decisions. Because value does not come from discovering more possibilities. It comes from executing the right ones better.
"Nearly a Terawatt" (~900 gigawatts) vs US 2024 Capacity of 1.25 TW. For comparison, average US Power Consumption = 500 GW of 1/2 TW. Yet, interconnection queues are notoriously bloated — historically only 20-30% of queued projects ever get built - ah, we hope. The staggering implication: if even 1/2 of the map gets built and powered primarily by NG, it would roughly double current US power-sector gas consumption. In 2011, MIT published a landmark report, "The Future of Natural Gas," coining NG as a "bridge fuel", MIT co-chair, Henry Jacoby stated: "People speak of gas as a bridge to the future, but there had better be something at the other end of the bridge." Yet, bridges take time - that we ain't got.
Matthew Kilkenny are you using AI to write your pieces?
As someone that's studying Computer Science, was this really a shock? I would think that this guy was studying the latest information, right, and not a course that was already outdated... Yes it is sad but being surrounded by other techies, why didn't the Computer Science degree support new technology? What am I missing here?
Michelle L. I agree totally! It would be like learning how to use a typewriter and then complaining that computers are now replacing them! I would surly think that doing a computer science degree was to learn the latest tech and not what would become obsolete.