Demi

Energy||AI/ML||Data science||Art.

Love yours❤️

[Demi @Demi_jd01]

@Omah_Lay Omah lay tweeting this just a few days after he was locked up with Tems

[Demi @Demi_jd01]

@_miideey Now it has become slow

[Demi @Demi_jd01]

@_miideey You didn’t strike me as a troublesome/mischievous student😂

[Demi @Demi_jd01]

@Dacron4show Joy just wan kill you

[Demi @Demi_jd01]

@em07_adoz Congratulations!

[Demi @Demi_jd01]

@sammyabams Agba Alhaji

[Demi @Demi_jd01]

@buildanythingso Interested

[Demi @Demi_jd01]

@_miideey This!
Later they’d say Lagos is smelling when they’re also part of the problem

[Demi @Demi_jd01]

@_miideey Knowing the backstory🤣>>>

[Demi @Demi_jd01]

@lgnd_craft Congratulations bro

[Demi @Demi_jd01]

@Rondal9147 @fcb_dexx @grok Thank you

[Demi @Demi_jd01]

@_miideey It’s not easy

[Demi @Demi_jd01]

@NShiaki Happy birthday🎂✨

[Demi @Demi_jd01]

@_miideey Please don’t mislead people😂😂

[Cxspxxr✘🧸 @_6signxxx]

tbh this is peak evidence that life’s gotten painfully boring. god i miss treeeeeees man

[Demi @Demi_jd01]

@_miideey Thisss was so sad

[Tech with Mak @techNmak]

It is dangerously easy to build a neural network today without actually understanding how it works.

We live in an era of 'import torch'. You can train a model in three lines of code, but the moment you need to debug a collapsing loss function or a vanishing gradient, syntax won't save you. You need first principles.

I recently went through this notebook collection by Simon J.D. Prince, and it is the antidote to tutorial hell.

Instead of just showing you the code, it forces you to visualize the mechanics:
1./ The Math => It builds the intuition for shallow networks and regions before adding complexity.
2./ The Optimization => It doesn't just use an optimizer; it compares Line Search, SGD, and Adam so you see why they behave differently.
3./ The Modern Stack => It connects the dots from basic backpropagation all the way to Self-Attention and Graph Neural Networks.

Move from running code to engineering systems => this is a goldmine.

[Palm Rail @usepalmrail]

Palm Rail is here! 🌴💼

A $PUSD work-settlement rail for cross-border services on Solana.

One program-owned vault. Milestone PDAs. Evidence hashes. Role-scoped signing. Token-2022 compatible flow.

[Akshay 🚀 @akshay_pachaar]

As an AI Engineer. Please learn:

- Harness engineering, not just prompt engineering
- Prompt caching vs. semantic caching tradeoffs
- KV cache management at scale
- Speculative decoding vs quantization
- Structured output failures & fallback chains
- Evals (LLM-as-judge + human evals)
- Cost attribution per feature, not just per model
- Agent guardrails & loop budgets
- LLM observability as a first-class discipline
- Model routing & graceful fallback logic
- Knowing when to fine-tune vs. in-context learning