HN is the way I keep up with what’s going on. AI is very much the topic of the moment. I’m fine with it the way it is.
1,730 karma · joined August 5, 2010
This book helped me put it in perspective: https://pragprog.com/titles/cfcar2/the-passionate-programmer...
2. Propose a solution to the problem and get feedback.
3. Design the data model(s) and get feedback.
4. Design the system architecture and get feedback.
5. Design the software architecture and get feedback.
6. Write some code and get feedback.
7. Test the code.
8. Let people use the code.
Writing the code is only one step.
In all honesty, I expect over time intelligent agents will be used for the other steps.
But the code is based on the proposed solution, which is based on the problem statement/requirements. The usefulness of the code will only be as good as the solution, which will only be as good as the problem statement/requirements.
It’s a weird feeling seeing my feed (I made a new account to view content shared via tweet because the feed is no longer public) and having no control over it.
You can’t trust an administration that would release a report that cites sources that do not exist. They are either so incompetent that they cannot perform the most basic fact checking possible, or they think we are idiots who can be easily misled.
I remember going to a cloud meetup in the early days of AWS. Somebody said "you won't need DBAs because the database is hosted in the cloud." Well, no. You need somebody with a thorough understanding of SQL in general and your specific database stack to successfully scale. They might not have the title "DBA," but you need that knowledge and experience to do things like design a schema, write performant queries, and review a query plan to figure out why something is slow.
I'm starting to understand that you can use a LLM to both do things and teach you. I say that as somebody who definitely has learned by struggling, but realizes that struggling is not the most efficient way to learn.
If I want to keep up, I have to adapt, not just by learning how to use tools that are powered by LLMs, but by changing how I learn, how I work, and how I view my role.
That's why I think it's a matter of mindset. This is going to sound dumb, but I keep thinking about the interactions between Robert Downey Jr. as Tony Stark and Jarvis in Iron Man. That's the AI I always wanted: something that could do deterministic (here's the weather, here's your schedule) and non-deterministic (research) things.
Jarvis wasn't the inventor. Jarvis was a tool Tony used to invent things.
There is no reason to think the current Administration will not continue to use this tactic.
[0] - https://en.wikipedia.org/wiki/Detention_of_Mahmoud_Khalil
"The Apple focus group was the right hemisphere of Steve’s brain talking to the left one."
If you don't incorporate data into your product devisions, you're going to have a bad time.
If you only incorporate data into your product decisions, you're going to have a bad time.
If you balance left and right brain thinking, you might come up with a successful product.
I had a similar idea. I have enough experience with visual programming environments to be wary. Here are my thoughts on why it might be a good approach here: * It would be possible to take a whiteboard scribble and turn it into a real system. Combining this with the services available in the cloud, you end up with something really powerful. It all comes down to the level of abstraction supported. You have to be able to draw boxes at a level that adds value, but also zoom in to parameters at the service/API level as necessary. * I've worked on a team that was responsible for designing and maintaining its own AWS infrastructure. Along with that comes the responsibility for controlling cost. The idea of having a living architectural diagram that also reported cost in near real-time is really helpful, especially if you could start to do things like project cost given a level of traffic or some other measure.
Once you have a decent library of TF modules, and an understanding of the networking and compute fundamentals, and an understanding of the services offered by your cloud provider, you have something really powerful. If a service can help accelerate that, it's worth it IMHO.
I really appreciate how the NWS products make it easy to create custom widgets that you can embed in a webpage.
I don't know if they're using a LLM specifically, as opposed to say computer vision models or some other method.
Pricing: https://azure.microsoft.com/en-us/pricing/details/cognitive-...
AWS has something similar: https://aws.amazon.com/rekognition/content-moderation/