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Also: https://archive.vn/evQgH
archive.vn has never loaded for me; a lot of the time it doesn't even resolve
I don't know anything about this company. But I work at FAANG as an ML scientist and spent about 3 months this year working on a research project that demonstrated big performance improvements of a new tech. It got enough interest that it led to a new project that brings this to production. This has led to countless headaches. The skills needed to solve these challenges are very different. My more academically minded…
Indeed. I founded a contactless personalized food production and automation robotics venture in 2016. We tore through specialist and generalist employees alike trying to make progress toward a final prototype. We're now essentially there, but lost the team over COVID, while the investment environment for our technology is currently extremely hot. In taking stock of the situation to move forward, I've realised it's actually a blessing: the skills needed to reach mass-production on a very complex assembly are very different to the skills needed to iterate early and mid-stage prototypes rapidly and effectively. It would have literally been harder - and more expensive - to drag people 'over the line' in to production than to just hire a new team.
Unlike Landing.ai and C3.ai, Element.ai was lacking of a solid go-to-market strategy from day 1.
> Unlike Landing.ai and C3.ai... What do you believe the go-to-market strategy is of those two? For C3.ai, my interpretation was they're trying to become the Microsoft of ML, re-packaging the entire ML pipeline into a more consumable developer experience. They seem currently focused more upon the model analytics part of the pipeline than say, training data selection or ETL to ingest raw data (whether to train upon or…
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Really good insight. When I put engineering job posts up, we get loads of PhD applications...a staggering amount. And all of these people look great on paper. It’s only when you start talking to them off script that you understand a career in academia has radically different incentive pressures than the private sector. We end up passing on most, not because they aren’t brilliant, but because they’re very one dimensio…
It must be surprising to find "brilliant" people who are apparently incapable of learning how to do new things.
I'm not saying that the OP should hire these people, or that they would even be good hires. Maybe they don't want to take the risk or time of training up a new employee.
It just seems like a bit wierd non-sequitur to draw conclusions on someone's learning capabilities based on their performance in an interview outside their usual domain.
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It must be surprising to find "brilliant" people who are apparently incapable of learning how to do new things.
I don't think it's fair to characterize such people as "incapable of learning how to do new things" if they're not even being given the opportunity to learn. I'm not saying that the OP should hire these people, or that they would even be good hires. Maybe they don't want to take the risk or time of training up a new employee. It just seems like a bit wierd non-sequitur to draw conclusions on someone's learning capabi…
Earlier quoted context omitted.
Really good insight. When I put engineering job posts up, we get loads of PhD applications...a staggering amount. And all of these people look great on paper. It’s only when you start talking to them off script that you understand a career in academia has radically different incentive pressures than the private sector. We end up passing on most, not because they aren’t brilliant, but because they’re very one dimensio…
It must be surprising to find "brilliant" people who are apparently incapable of learning how to do new things.
So much for Montréal becoming the Silicon Valley for AI. Another Canadian/non-Californian startup bites the dust.
I don't know anything about this company. But I work at FAANG as an ML scientist and spent about 3 months this year working on a research project that demonstrated big performance improvements of a new tech. It got enough interest that it led to a new project that brings this to production. This has led to countless headaches. The skills needed to solve these challenges are very different. My more academically minded…
So they got the idea, that they could hire other STEM Master's and PhD's, offer them an average software engineer salary and train them up to become good software engineers. Many software engineers scoffed at the idea - so you're hiring people from Physics to do web apps - pfff, what do they know about creating software?
Well, I'd say a third of my coworkers at the time were from "academia" - I felt absolutely no difference. The company is thriving and they have more than quadrupled in size since I worked there five years ago.