🚨 OPEN SOURCE AI IS LITERALLY UNSTOPPABLE 🚨
The legendary founder of Redis (Antirez) just dropped ds4 - a custom native inference engine built specifically for DeepSeek v4 Flash
This is earth shattering! Here is why:
DeepSeek v4 Flash is a quasi-frontier model with a massive 1M context window
You can now run it LOCALLY on a 128GB Mac using specialized 2-bit quantization
The architecture is reimagined—he moved the KV cache from RAM directly to the SSD disk! 🤯
We already know DeepSeek v4 Flash is insanely good for agentic loops - Now you don't even need the cloud to run it
Closed-source labs are burning tens of billions on massive GPU clusters while single brilliant developers are running frontier-level AI on laptops!
They told us open-source would be worthless against trillion-dollar monopolies
Instead, pure hacker culture + incredible open-weight models are completely rewriting the rules
Open Source will ALWAYS win 💕
@chiragbarjatya Cockroaches enter through drains or from already laid eggs. Drainex/caustic soda in every drain + proper sealed (but removable) covers with no gaps. Do 3x over 2 months. No food left out overnight. Pest control only works once for eggs — after that, seal the source permanently.
Similarly LLMs is an approximation of the actual way we process knowledge. Karpathy called them ghosts - and not real animal-like intelligence. Important distinction.
Any kind of neural network is an approximation function of a real-world function f(x) = y. Since we don't know this f(x) - we approximate using weighted smaller fns. I find this explanation helps for non-CS techies to understand how LLMs/CNNs/RNNs work.
(1/2)
For example we don't know what is the mathematical representation of human brain object detection or object labelling - CNNs approximate that behaviour
Mumbai teaches you that "space" is a luxury, but "grace" is a choice. You can be pushed by 500 people in a local train and still find someone who offers you their seat because they see you're tired. The city is rough, but the people are soft.
Few months back, we took an audacious target of solving 95 percent service requests and installation requests within 24 hours in all metro and tier 1 cities. The industry standard TAT is 72 hours
In January, we achieved 89 percent
When the rest of the industry focuses on marketing campaigns for demand, our focus has always been on how to delight consumers post purchase through exceptional service
And if you do this well, word of mouth follows and brands grow, specially in categories like ours
After sales service at Atomberg has always been a part of marketing. The budget is always a combined budget. It is a front end budget, not a cost to be optimized
I still spend couple of hours every week replying to customer queries on DM or taking customer calls, and is also the part which i enjoy the most
There is a gold-rush in PM jobs. I see folks giving one-stop solution on becoming a PM. Probably already more folks teaching how to be a PM than number of the jobs in the market.
My manager once said, "Product Management has to be learnt by doing..." - still rings true today.
Launch something tasteful, distinct, noteworthy, not merely useful and viable.
It’s not 2014 where you ‘launch any MVP to just learn from early adopters’ and hope to win from there on
@smallcase 3/8 Think of smallcases as ready-made portfolios curated by SEBI-registered experts. As you buy more such portfolios - and rebalance regularly - one can achieve diverse portfolios that are typically exclusive to select few. Disclaimer: smallcases are also subject to market risks.
@smallcase 2/8 But first, what is smallcase. Smallcase offers a basket of stocks developed over a theme or idea. Example, a stock basket on the theme of Green Energy benefits from the developments in the Renewable Energy Sector
What’s better is that only fifteen masterpieces will ever be made, making each piece a gem that will never be replicated.
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