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Andrew Ng: Building Faster with AI [video]

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Re: Andrew Ng: Building Faster with AI [video]

#61

Post by alex_smart »

lloeki wrote: post #57
w10-1 wrote: post #7

Not sure why this has drawn silence and attacks - whence the animus to Ng? His high-level assessments seem accurate, he's a reasonable champion of AI, and he speaks credibly based on advising many companies. What am I missing? (He does fall on the side of open models (as input factors): is that the threat?) He argues that landscape is changing (at least quarterly), and that services are (best) replaceable (often week…

> AOP? (since aspect-oriented programming is history) AOP is very much alive, people that do AOP have just forgotten what the name is, and many have simply reinvented it poorly.

Also very much alive and called that in the Java/Spring ecosystem

Re: Andrew Ng: Building Faster with AI [video]

#62

Post by fullstackchris »

lubujackson wrote: post #16
w10-1 wrote: post #7

Not sure why this has drawn silence and attacks - whence the animus to Ng? His high-level assessments seem accurate, he's a reasonable champion of AI, and he speaks credibly based on advising many companies. What am I missing? (He does fall on the side of open models (as input factors): is that the threat?) He argues that landscape is changing (at least quarterly), and that services are (best) replaceable (often week…

I'm guessing because this is basically an AI for Dummies overview, while half of HN is deep in the weeds with AI already. Nothing wrong with the talk! Except his focus on "do everything" agents already feels a bit stale as the move seems to be going in the direction of limited agents with a much stronger focus on orchestration of tools and context.

> deep in the weeds with AI already

I doubt even 10% have written a custom MCP tool... and probably some who don't even know what that means

Re: Andrew Ng: Building Faster with AI [video]

#63

Post by rhizome31 »

hakanderyal wrote: post #20
lubujackson wrote: post #16

Earlier quoted context omitted.

I'm guessing because this is basically an AI for Dummies overview, while half of HN is deep in the weeds with AI already. Nothing wrong with the talk! Except his focus on "do everything" agents already feels a bit stale as the move seems to be going in the direction of limited agents with a much stronger focus on orchestration of tools and context.

From the recent threads, it feels like the other half is totally, willfully ignorant. Hence the responses.

As someone who is part of that other half, I agree.

Re: Andrew Ng: Building Faster with AI [video]

#64

Post by skipants »

I’m 20 minutes into the video and it does seem mostly basic and agreeable.

Two arguments from Ng that really stuck out that is really tripping my skepticism alarm are:

1) He mentions how fast prototyping has begun because generating a simple app has become easier with AI. This, to me, has always been quick and never the bottleneck for any company I’ve been at, including startups. Validating an idea was simple enough via wireframing. I can maybe see it for selling an idea where you need some amount of fidelity yo impress potential investors… but I would hope places like YC can see the tech behind the idea without seeing the tech itself. Or at least can ignore low fidelity if a prototype shows the meat of the product.

2) Ng talks about how everyone in his company codes, from the front desk to the executives. The “everyone should code” idea has been done and shown to fail for the past 15 years. In fact I’ve seen it be more damaging than helpful because it gave people false confidence that they could tell engineers how to do their job rather than a more empathetic understanding.

Re: Andrew Ng: Building Faster with AI [video]

#65

Post by stego-tech »

vlovich123 wrote: post #41
stego-tech wrote: post #13

Earlier quoted context omitted.

> So: what platforms are available? I couldn't tell you, but what I can contribute to that discussion is that orchestration of AI in its current form would focus on one of two approaches: consistent output despite the non-deterministic state of LLMs, or consistent inputs that leans into the non-deterministic state of LLMs. The problem with the former (output) is that you cannot guarantee the output of an AI on a cons…

> The problem with the former (output) is that you cannot guarantee the output of an AI on a consistent basis Do you mean you cannot guarantee the result based on a task request with a random query? Or something else? I was under the impression that LLMs are very deterministic if you provide a fixed seed for the samplers, fixed model weights, and fixed context. In cloud providers you can't guarantee this because of h…

> I was under the impression that LLMs are very deterministic if you provide a fixed seed for the samplers, fixed model weights, and fixed context.

That's all input-side, though. On the output side, you can essentially give an LLM anxiety by asking the exact same question in different ways, and the machine doesn't understand anymore that you're asking the exact same question.

For instance, take one of these fancy "reasoning" models and ask it variations on 2+2. Try two plus two, 2 plus two, deux plus 2, TwO pLuS 2, etc, and observe its "reasoning" outputs to see the knots it ties itself up in trying to understand why you keep asking the same calculation over and over again. Running an older DeepSeek model locally, the "reasoning" portion continued growing in time and tokens as it struggled to provide context that didn't exist to a simple problem that older/pre-AI models wouldn't bat an eye at and spit out "4".

Trying to wrangle consistent, reproducible outputs from LLMs without guaranteeing consistent inputs is a fool's errand.

Re: Andrew Ng: Building Faster with AI [video]

#66

Post by techpineapple »

void-star wrote: post #47
imranq wrote: post #32

My two takeaways is you build 1) Having a precise vision of what you want to achieve 2) Being able to control / steer AI towards that vision Teams that can do both of these things, especially #1 will move much faster. Even if they are wrong its better than vague ideas that get applause but not customers

Yes this! The observation that being specific versus general in the problems you want to solve is a better start-up plan is true for all startups ever, not just ones that use LLMs to solve them. Anecdotal/personal startup experiences support this strongly and I read enough on here to know that I am not alone…

What's the balance between being specific in a way that's positive and allows you to solve good problems, and not getting pigeonhold and not being able to pivot? I wonder if companies who pivot are the norm or if you just here of the most popular cases.

Re: Andrew Ng: Building Faster with AI [video]

#67

Post by apwell23 »

skipants wrote: post #64

I’m 20 minutes into the video and it does seem mostly basic and agreeable. Two arguments from Ng that really stuck out that is really tripping my skepticism alarm are: 1) He mentions how fast prototyping has begun because generating a simple app has become easier with AI. This, to me, has always been quick and never the bottleneck for any company I’ve been at, including startups. Validating an idea was simple enough…

even prototyping hasn't become "fast" because you cannot purely vibecode even a prototype.

Re: Andrew Ng: Building Faster with AI [video]

#68

Post by markerz »

croes wrote: post #15

I haven’t watched the video yet, but title does sound like quantity over quality. Why faster and not better with AI?

I think quality takes time and refinement which is not something that LLMs have solved very well today. They are very okay at it, except for very specific targeted refinements (Grammerly, SQL editors).

However, they are excellent at building from 0->1, and the video is suggesting that this is perfect for startups. In the context of startups, faster is better.

Re: Andrew Ng: Building Faster with AI [video]

#69

Post by croes »

pinkmuffinere wrote: post #56
croes wrote: post #15

I haven’t watched the video yet, but title does sound like quantity over quality. Why faster and not better with AI?

I think this is an interesting question, and I’d like to genuinely attempt an answer. I essentially think this is because people prefer to optimize what they can measure. It is hard to measure the quality of work. People have subjective opinions, the size of opportunities can be different, etc, making quality hard to pin down. It is much easier to measure the time required for each iteration on a concept. Additionall…

I think speed isn’t our problem.

Most of the time the problem it‘s quality but everyone only seems eager to ship as fast as possible.

Move fast and break things already happened and now we are adding more speed.

„Your scientists were so preoccupied with whether they could, they didn't stop to think if they should."

Or for the more sophisticated

https://en.wikipedia.org/wiki/The_Physicists

Energy consumption and data protection were a thing and then came AI and all of a sudden it doesn’t matter anymore.

Between all the good things people create with AI I see a lot more useless or even harmful things. Scams and fake news get better and harder to distinguish to a point where reality doesn’t matter anymore.

Re: Andrew Ng: Building Faster with AI [video]

#70

Post by croes »

markerz wrote: post #68
croes wrote: post #15

I haven’t watched the video yet, but title does sound like quantity over quality. Why faster and not better with AI?

I think quality takes time and refinement which is not something that LLMs have solved very well today. They are very okay at it, except for very specific targeted refinements (Grammerly, SQL editors). However, they are excellent at building from 0->1, and the video is suggesting that this is perfect for startups. In the context of startups, faster is better.

Depends on the startup. For medical or financial things faster isn’t better.

DOGE acts like a startup and we all fear the damage.

I would prefer better startups over faster at anytime.

Now I fear AI will just make the haystack bigger and the needles harder to find.

Same with artists, writers, musicians. They drown in the flood of the AI created masses.

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