Shishir bhat

Developer, Investor, Research, Antifragile, Learning Machine

[Javier Blas @JavierBlas]

As I indicated in my previous post, the U.S. Treasury confirms the U.S. is lifting sanctions on Russian diesel exports (including into the U.S.) until April 2027.

[Shishir bhat @shiihsr]

@Krishnarajk22 This reminds me of Howard Marks. He says the outcome shouldn't judge whether your process was right or wrong. You could just be lucky with the wrong process and still win and vice versa. Very tough to judge the process without the outcome though.

[Shishir bhat @shiihsr]

Seeing causal opacity in action. When the markets go up, we tend to find good things to attribute it to. When the markets go down, we tend to find the bad things. But nothing has changed a lot in this short time. Serving our flaws very well.
#Markets #Nifty

[Rohit @L_TheAnalyst]

AI models are trained once. So why does GPU demand keep growing?

This was one of the questions I wanted to understand while studying companies like E2E Networks and ESDS.

The simple answer is that AI needs GPUs for two very different things.

Training and inference.

Let me explain this in the simplest way possible.

Training is when an AI model learns from huge amounts of data.

That process needs massive computing power because GPUs can do many calculations in parallel.

That is why large AI models need thousands of GPUs during training.

But training is only one part of the story.

The more interesting part is inference.

Inference simply means people actually using the trained AI model.

You type a question into ChatGPT.

Someone generates an image.

A company runs an AI agent.

Another user uploads a document and asks for analysis.

All of these requests need compute.

And when millions of users are sending requests at the same time, the model needs huge GPU capacity just to respond quickly.

So you can think about it like this.

Training is heavy compute used to build the model.

Inference is recurring compute used every time people use the model.

And inference demand keeps increasing because

More people are using AI

AI applications are increasing

Models are becoming more capable

Context lengths are becoming larger

Users are sending more requests

AI agents are doing multiple tasks automatically

This is why GPU demand is not only dependent on new models being trained.

Even after a model is trained, serving millions of users creates continuous demand for compute.

This is where companies like E2E Networks and ESDS become interesting.

They provide access to GPU infrastructure to companies that need AI compute without buying and managing all the GPUs themselves.

So the AI demand chain becomes simple.

More AI models

More training

More users

More inference

More GPU compute required

That is the basic reason GPU demand continues to grow.

There is much more depth to this, but understanding training and inference first makes the entire GPU cloud opportunity much easier to understand.

#E2ENetworks #ESDS

[Shishir bhat @shiihsr]

Change is like heaven. Everyone wants to go there, but nobody wants to die. - Breaking History(Jared Kushner)

[Krishna Raj K @Krishnarajk22]

#Fitnessbands might help you monitor you sleep, heart rate and all, but what if i told you in a longer term if the parameters in your watch are not so good, you might be rejected from getting an insurance.

[Shishir bhat @shiihsr]

@SureshKBN Also, cloudfare announced they are getting into becoming a CA themselves.

[Shishir bhat @shiihsr]

You still make errors when your predictions are unbiased, but the errors are smaller and do not favor either high or low outcomes - Daniel Kahneman in Thinking Fast and Slow.

As a human, it's impossible to predict without being biased.

[Shishir bhat @shiihsr]

Changing one's mind about human nature is hard work, and changing one's mind for the worse about oneself is even harder - Daniel Kahneman from Thinking Fast and Slow

That is why we assume we belong to the outlier group in any random field we want to step in.

[Shishir bhat @shiihsr]

One thing that AI is still lacking is to come up with an essay like the one written by @paulg https://t.co/Nc8UVQDuzt

Similarly, the knowledge of I having some knowledge of a thing also cannot be replicated by AI.

[Shishir bhat @shiihsr]

The main thing from hereon is the execution and how large can the value added products become as a % of revenue. That will tell us whether Margin expansion is visible or not.

[Shishir bhat @shiihsr]

Sunflag has got these approvals, VSSC, LPSC (both ISRO) in the space segment, approvals from HAL, BrahMos, DRDO, DRDL, Solar Industries, Paras Defence, HYT Innovatives, Adani Defence and other global OEMs. Out of all NADCAP is the most important.
#sunflag

[Shishir bhat @shiihsr]

But what is interesting is that the AR reveals 10T solution annealing and 20T electric annealing furnaces for superalloys under installation which is a good enough assumption for commercialization.

[Shishir bhat @shiihsr]

Here's my new blog on decision making and investing https://t.co/ddCknYUHQo

[Zeno @Zenovibez]

I’m only quiet around people I don’t vibe with. Catch me with my people and it’s a whole different story.

[Shishir bhat @shiihsr]

@unseenvalue Got the answer to my previous question sir. Thank you sir

[Shishir bhat @shiihsr]

@MahaAmatya A nyaya sudha student can win any logical argument

[Stijn Noorman @stijnnoorman]

Shamelessly promote yourself.

The world is full of incompetent people who aren't ashamed to promote themselves.

So if you're competent, it's your obligation to promote yourself.

[Shishir bhat @shiihsr]

How many of you are willing to take a bet on someone who's taking a bet on his career/life?