This is a good tooling survey of the past year. I have been watching it as a developer re-entering the job market. The job descriptions closely parallel the timeline used in the post. That's bizarre to me because these approaches are changing so fast. I see jobs for "Skill and Langchain experts with production-grade 0>1 experience. Former founders preferred". That is an expertise that is just a few months old and startups are trying to build whole teams overnight with it. I'm sure January and February will have job postings for whatever gets released that week. It's all so many sand castles.
No idea about training tenserflow models - is it super complex or is it just calling a couple of APIs ? Langchain is literally calling an API. Maybe you need to get good with prompting or whatever, but I don't see where the complexity lies. Please let me know.
Having used both Tensorflow (though I expect they mean PyTorch which is way more popular, and I have also used) and langchain, they are nothing alike.
They he ML frameworks are much closer to implementing the mathematics of neural networks, with some abstractions but much closer to the linear algebra level. It requires an understanding of the underlying theory.
Langchain is a suite of convenience functions for composing prompts to LLMs. I wouldn’t consider there to be some real domain knowledge one would need to use it. There is a learning curve but it’s about learning the different components rather than learning a whole new academic discipline.
You're right, none of these new tools are disciplines. They are vendor specific approaches that are very recent. That's part of my overall point. Who is out there with 2+ years of very narrow tooling experience at another company at a senior level and is available for a rando startup (or desparate enterprise looking for bolt-on AI features) at a fraction of the pay? Not many, I'm sure. We can level up, do training, and maybe stand up a demo project. But that won't satisfy an ATS scan. It's unrealistic.
There's a big difference between building an ML framework like Tensorflow or PyTorch (I built a Lua Torch-like one in C++ myself) and just using it to build/train a model.
Building the model may range from very simple if you are just recreating a standard architecture, or be a research endeavor if you are designing something completely new.
The difficulty/complexity of then training the model depends on what it is. For something simple like a CNN for image recognition, it's really just a matter of selecting a few hyperparameters and letting it rip. At the other end of the spectrum you've got LLMs where training (and coping with instabilities) is something of a black art, with RL training completely different from pre-training, and there is also the issue of designing/discovering a pre/mid/post training curriculum.
But anyways, the actual training part can be very simple, not requiring too much knowledge of what's going on under the hood, depending on the model.
There are multiple services that verify and rate NGOs and nonprofits. The key is to look them up on the service website and not just Google the name. Personally I use Guidestar, but that's for U.S. orgs.
True. People define the speech of others as violence because they think it makes a violent response into self defense. It isn't true and never has been. If you're responding to speech with violence... you're the baddie.
I think packetlost knows that. I think the argument being put forward was that "if you are the kind of person that thinks that speech is violence, then you would believe that allowing someone a platform..."
This is not a general problem with moderation there, centralized or decentralized. This particular issue is specific to a large group of people that don't like Jesse Singal and have been trying to get him removed from Bluesky. It hasn't worked and that group is trying all kinds of way to reframe the narrative to get leverage. All the padding this post adds around that is neotechnical jargon slop.
The more interesting part of the article, completely unrelated to Jesse Singal, is that Bluesky bans also apply to Blacksky because Blacksky can't afford to run their own moderation.
According to the post, it's a usability issue of the open source app layer and not some failure of moderation principles. "Blacksky is dependent on Bluesky’s application server to give users a fast experience, which also means that it is dependent on Bluesky’s labeling system and its moderation choices." Also, Singal's name is mentioned multiple times throughout the the article in irrelevant contexts. I still see the agenda here and I've seen this tactic before.
Social media hasn't been social for a while. Personal posts from people I know are buried under the algorithms. It's a high friction action to actually find my friends. All the defaults are pointed at optimized content from generic sources. I have many friends that are artists and musicians. I follow them on these platforms and my engagement with them is captured and funneled into garbage content about art and music instead of letting my see my friends. I hate it.
This about pitching, not about building. What you can put in a vibe coded demo and a slide deck versus what functions in production a year later are very different. "Three Stanford kids in a trenchcoat" will always be able to get some kind of funding. That's less about technology and business principles and more about the legacy of P. T. Barnum.
Forget about AI and vibe coding and consider that those three Stanford grads might genuinely have found a way to deliver a significantly better product that will put your product out of business. The challenge then is this: How much of your yearly spend should you dedicate to researching these potential improvements yourself? Should you try to be an “early adopter” or a “late mover”?
After watching so many work chats disintegrate from politics, social commentary, or pedantic arguments I have totally avoided all unstructured channels. Since 2020 I saw two people get fired after discussions got out of hand. There were many more team meetings, code of conduct edicts, and all hands declarations about communication issues. It wasn't until the bans on politics in Slack arrived until things got better. Even now there are people I will screenshot any DMs that have even a hint of conflict. I doubt I will ever participate in any work chats in a social way again.
There's a distinction between random (probably not for work, 'water cooler chat') and 'obviously divisive' topics like politics. Particularly in the US, those are the sort of things you avoid.
Must depend on the company/office. My team (200+ people) has a "offtopic/socialize" chat channel set up for this kind of rando chit chat, and it has never, not once in many years, even had a hint of divisiveness or politics. Yes, you do need to be working with grownups who can behave and leave that shit at home.
Thanks for that link. Wow, what a wild story. I agree with the top commenter: It looks like the company was composed entirely of children or adults with child-like communication skills/habits!
Huh? Thats just not true. We have channels for gamers, pets, golf, home automation, “lounge”, “memes”, etc. I’ve been at this company 4 years and can only thing if 3 times I’ve seen a dispute, and even that was very civil. It’s really not hard to leave politics at home.
Never do casual conversation on the record. It's always going to result in this kind of stuff. If you want to get to know your coworkers, go out to lunch with them or chat face to face. That way you can limit exactly who is listening, gauge the response. And anything you say will be lost to time.
Obviously you can still get in trouble if you say something very inappropriate, but anything middle of the road will be forgotten.
An underreported part of the Yahoo story is its relationship to India. I worked there during the Verizon years and heard the history. Yahoo was a forerunner of the "offshoring" of technology jobs to India. It moved lots of core operations to a small army of engineers there. They figured out that their American counterparts made substantially more money than they did, especially the middle managers. Waves of Indian employees began moving to Santa Clara and getting market rate wages. Suddenly, Yahoo wasn't saving as much money as they used to. I don't think it was a major factor in its overall financial decline, but it had some effect I'm sure. On a side note, I heard a couple of Indian engineers say they were moving back to raise their kids because they didn't like the cultural influences in our schools. There were many interesting lunchtime conversations about things like that.
> On a side note, I heard a couple of Indian engineers say they were moving back to raise their kids because they didn't like the cultural influences in our school
They didn't like the cultural influences by a culture which advanced their life prosperity so they relocate their children back to the culture where they will have to learn everything again by themselves.
My last job had a team with about 50% temp and contract. When the LLMs got popular, I could tell right away. When I reviewed their code, it was completely different than their actual style. The seniors pushed back because it was costing us more time to review and we knew it was generated. Also, they couldn't talk about about what they did in meetings. They didn't know what it was really doing. Eventually the department manager got tired of our complaining and said "it's all inevitable." Then those mercenaries started to just rubber stamp each other's PRs. The led to some colossal fuckups in production. Some of them were fired quietly, and the new people promptly started doing the same thing. Why should they care, it's just a short term contract on the way to the big payday, right?
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