Hacker News: rjdagost

New comment by rjdagost in "Update on Llama adoption"

rjdagost — Thu, 29 Aug 2024 15:29:43 +0000

Meta has spent massive sums of money to train these models and they've released the models to the public. You can fine-tune the models. You can see the source code and the architecture of the model. The EULA is commercially-friendly.

You are free to quibble over how truly "open source" these models are, but I am very thankful that Meta has released them.

New comment by rjdagost in "12 years since Saab’s bankruptcy: Secret NEVS electric cars revealed"

rjdagost — Fri, 26 May 2023 14:46:01 +0000

SAAB was financially failing when GM bought them. It's tough to blame GM for trying to impose financial discipline on a money-bleeding operation.

New comment by rjdagost in "New York set to ban gas furnaces, stoves in new buildings"

rjdagost — Sat, 29 Apr 2023 17:33:56 +0000

Then there's the question of how the electric grid will sustain this significant new increase in demand. As with mandates banning gas cars, the grid supply and stability is always regarded as a mere detail to be sorted out later.

New comment by rjdagost in "Ask HN: I have diagnosed ADHD and cannot work with Slack anymore – advice?"

rjdagost — Fri, 16 Dec 2022 23:10:12 +0000

Slack is great in small doses, but a complete time-waster beyond a certain threshold. I don't have ADHD, but I still have had problems with Slack. Don't feel bad about shutting all notifications off, or, better yet, closing the app entirely, and only opening it once or twice a day. You will almost instantly feel better. Some people may get annoyed that you're not instantly available, but if you're not able to get your work done then many more people will get annoyed. There is no perfect solution.

New comment by rjdagost in "CRISPR cancer trial success paves the way for personalized treatments"

rjdagost — Thu, 10 Nov 2022 23:23:10 +0000

I have worked in both semiconductor manufacturing and drug discovery industries. Reliably and profitably producing 5 nm chips is an extreme engineering challenge, but- it is an engineering challenge. Drug discovery is a question of science and requires a fundamentally different mindset that semiconductor manufacturing. Human biology is much more complicated than manufacturing chips (and that is extremely complicated); drug discovery is about "unknown unknowns". Discovering a drug that has the intended effects without causing terrible adverse effects is something that some of the best-funded companies on the planet struggle with.

New comment by rjdagost in "AI models that predict disease are not as accurate as reports might suggest"

rjdagost — Fri, 21 Oct 2022 20:00:03 +0000

If there's one thing I learned with biomedical data modeling and machine learning, it's that "it's complicated". For biomedical scenarios, getting more data is often not simple at all. This is especially the case for rare diseases. For areas like drug discovery, getting a single new data point (for example, the effect of a drug candidate in human clinical settings) may require a huge expenditure of time and money. Biomedical results are often plagued with confounding variables, hidden and invisible, and simply adding in more data without detection and consideration of these bias sources can be disastrous. For example, measurements from lab #1 may show persistent errors not present in lab #2, and simply adding in more data blindly from lab #1 can make for worse models.

My conclusion is that you really need domain knowledge to know if you're fooling yourself with your great-looking modeling results. There's no simple statistical test to tell you if your data is acceptable or not.

New comment by rjdagost in "The most dangerous road for cyclists in America"

rjdagost — Thu, 29 Sep 2022 03:59:48 +0000

One of the big differences between the US and Europe in this regard is the much larger proportion of bicyclists in Europe. In Europe, the larger number of bicyclists trains you as a driver to always be on the lookout for them. Driving past a bicyclist in the US is a much rarer event. Drivers should of course always be vigilant for anything in their way, but as a practical matter it's easier to mentally drift off when bicyclists are much less common.

New comment by rjdagost in "Saturated fat: villain and bogeyman in development of cardiovascular disease?"

rjdagost — Wed, 14 Sep 2022 17:56:06 +0000

With this kind of uncertainty, is it any wonder that many people don't trust medical science when we are told to behave in a certain way, or when we are told to take a certain medical treatment?

How many years have we been told that saturated fat is the nutritional devil? This is a great example of why censorship of "misinformation" is not justified- who is to say what constitutes misinformation?

New comment by rjdagost in "Ask HN: In 2022, what is the proper way to get into machine/deep learning?"

rjdagost — Tue, 16 Aug 2022 17:56:18 +0000

There is PhD level math involved. And yet, ML (deep learning in particular) is much more of an empirical endeavor than many would like to admit. A deep understanding of the underlying mathematics does not necessarily give you a better model. Modern models are so complicated that no one can reason through them. Parameter spaces are non-convex and fully of ugly pathologies that make neat and tidy analysis methods useless.

From one perspective, it is disheartening that a deep understanding of the underlying methods doesn't necessarily win the day. From another, it is quite remarkable that having good implementation skills and a methodical mindset can get you quite far.

New comment by rjdagost in "YOLOv6: Redefine state-of-the-art for object detection"

rjdagost — Wed, 29 Jun 2022 14:21:12 +0000

Calling YOLOv5 a "fraud" is a bit harsh. It has many excellent aspects for practitioners: easy to use, fast inference time, scalable model architecture, and it has many helpful utilities built-in for model deployment. In my experience, in real use-cases the models achieve about the same precision / recall / mAP as well as "state of the art" methods that report better stats on benchmarks.

New comment by rjdagost in "YOLOv6: Redefine state-of-the-art for object detection"

rjdagost — Wed, 29 Jun 2022 11:58:35 +0000

Welcome to computer vision / machine learning research!

New comment by rjdagost in "Tell HN: Turned 44 today and I'm lost"

rjdagost — Thu, 14 Apr 2022 17:18:20 +0000

What I'm hearing you say, loud and clear, is that you no longer have a sense of a purpose in life. Drugs (legal or otherwise) will not fill that void for you. I do not believe that you can rekindle a sense of purpose just by thinking about it. I would advise you to try new things that sound interesting to you, and keep exploring until you find something you can pour your heart and soul into. Probably something different from, or at least not directly related to, tech.

New comment by rjdagost in "AI startups raised $6.9B in Q1 2020"

rjdagost — Wed, 15 Apr 2020 14:01:57 +0000

I share your frustration. If you're trying to be realistic and straight-forward about the limitations of AI/ML, you're getting little interest from investors. Here's an anecdote. I was at an "AI in drug discovery" conference 2 years ago. One of the presenters, the founder of a drug discovery start-up, emphatically made the claim in a talk that "we should deliberately overhype AI in drug discovery, to raise awareness of what we as an industry can accomplish". I was gobsmacked by this. And yet, in the social mixer afterwards, the investors I spoke with LIKED this approach- they said the boastful founder was bold and visionary, and they didn't care that he was exaggerating the capabilities of his company. So, that's why all we hear is hype- founders are just responding to investor incentives.

That's also why I work as a freelance consultant and not as a founder. I think that autonomous driving (rather, the lack of such) is going to be what triggers the next AI winter. Too much money and hype, too little results for too long- the rope is wearing quite thin from what I can see.

New comment by rjdagost in "AI startups raised $6.9B in Q1 2020"

rjdagost — Wed, 15 Apr 2020 13:13:45 +0000

Your suspicion is largely correct, in my experience. I've worked as a consultant on a number of different AI / ML projects for start-ups. Most aren't doing anything all that new or groundbreaking from an ML point of view. Their real innovation is usually more about applying ML to industries / areas where it hasn't been used much before. But that doesn't get the investor dollars flowing in, so the founders try to make it seem like they have some radical new ML breakthrough. And in recent times, it has worked.

New comment by rjdagost in "Startups are pummeled in the ‘great unwinding’"

rjdagost — Sat, 04 Apr 2020 22:13:28 +0000

If there's one thing I've learned from the dotcom crash and the 2008 collapse, it's this: when the crap hits the fan, cash is king. Start-ups without profitable business models are extremely vulnerable. All of the pitches about exponential growth and glorious future profits carry little weight when investor psychology turns negative. So if you have a large pile of investor capital and you have investors who can't / won't claw their money back, you may be OK. But don't kid yourself that you are on an easier path.

New comment by rjdagost in "The patent on SIFT expired yesterday"

rjdagost — Mon, 09 Mar 2020 14:43:26 +0000

As a computer vision practitioner, I would argue that SIFT is still very relevant today. In most real-world scenarios it seems to hold up as well or better than the deep learning approaches I've tried, and it is easier to implement and maintain. Failures are often easy to understand and mitigate. In practice I often end up using FAST or ORB features due to "good enough" accuracy but much faster processing rates, especially on embedded devices. Feature detection and matching is an area where "classical" computer vision is very much alive and well.

New comment by rjdagost in "$50M worth of Tesla equipment sits unused in a Wheatfield warehouse"

rjdagost — Wed, 04 Mar 2020 21:41:35 +0000

You're trying to act like everything is A-OK with this project, when it has in reality been a huge waste of public money. First, there has already been a large corruption scandal centered on this project, with people in prison because of associated corruption (search Alain Kaloyeros). Second, those Tesla employment requirement milestones have been repeatedly reduced to require fewer jobs, and the types of required jobs has also been watered down. The requirements in the original agreement are more stringent than the 1460 jobs required now.

The state of NY just wrote off 92% of the value of its $957M investment in the factory: https://buffalonews.com/2019/11/08/pennies-on-the-dollar-the... Does that sound like Tesla is operating at 5/6 utilization of capital equipment?

Panasonic just announced that they're pulling out of the Buffalo factory: https://www.eveningtribune.com/news/20200227/after-nys-750m-... Tesla just wasn't giving them the business that they were promised in 2016 when they joined the project.

I had high hopes for this project when it was announced. It is near my hometown, and I thought it might be a good boost for the local economy. All it seems to have been is a big siphon from public funds, but not a siphon to where it is needed.

New comment by rjdagost in "$50M worth of Tesla equipment sits unused in a Wheatfield warehouse"

rjdagost — Wed, 04 Mar 2020 17:50:24 +0000

The history of the Buffalo "gigafactory" is rather sordid... In a nutshell, Tesla and its subsidiaries made large employment and economic growth promises to the state of NY in exchange for massive subsidies (almost $1B total). The state wanted to stimulate growth in an economically depressed region, but those growth expectations have not materialized at all. And now, at least some of the NY state taxpayer financed equipment is apparently being shipped elsewhere or sold instead of helping the economy of Western NY. That's the story here. But the entire story goes much deeper.

Tesla fans don't like to admit it, but the Buffalo "gigafactory" project has been a textbook example of government waste on corporate welfare. Multiple people have gone to jail for corruption / bid rigging on the project. Tesla's subsidies were supposed to be contingent on achieving hiring and economic output goals, but those original requirements have been retroactively watered down multiple times so as to prevent subsidy clawbacks. A local journalist (Dan Telvock) has been detailing considerably more chicanery that has gone done at the Buffalo gigafactory.

New comment by rjdagost in "Tesla Financial Results 2019 Q4"

rjdagost — Thu, 30 Jan 2020 02:19:21 +0000

This is what a speculative bubble looks like. Enjoy popcorn on the sidelines until people start pricing in financial reality. Manias sometimes take a while to fizzle out. Year over year revenue growth is actually flat to slightly negative for the past 2 quarters. If top-line revenue growth continues to stall out, that's often a catalyst for corrections.

New comment by rjdagost in "What’s wrong with computational notebooks?"

rjdagost — Tue, 28 Jan 2020 12:50:48 +0000

I have found PyCharm to offer a good trade-off between data exploration and productionizing your code. It has the best Python debugger that I've used. You can also run Jupyter notebooks in PyCharm when that makes sense for you.