Goody ↑ Startup Builder

Connected Economy ↑ Building with NEXTjs & Typescript. Developer @LarvrovHQ ↑ Maxxing

[Goody ↑ Startup Builder @goody_dev]

Learn, Build, Fund.

[Goody ↑ Startup Builder @goody_dev]

Consistency is boring, competency is fun.
The second is the result of the first.

[Goody ↑ Startup Builder @goody_dev]

Impractical ideas, practical steps.

[Goody ↑ Startup Builder @goody_dev]

Focus is the strength of execution.

[Goody ↑ Startup Builder @goody_dev]

You know where you are going?

Just start, and be prepared to do what it takes along the way.

[Popoola Oluwatemilorun @Themy046]

1/3 I’m Temilorun, full-stack dev (#Django + #React).
Building Inboxit: a dead simple tool that turns any website form into messages sent to your email/Slack/webhook.

No backend. No SMTP. No fetch/axios. Just drop the script and go.

[Goody ↑ Startup Builder @goody_dev]

At a mexc @MEXC_AfricaBU x axiflo @axioflo event.

#MexcEventRocks

[Goody ↑ Startup Builder @goody_dev]

Until you try building something on chain, you won't realise how costly and unsustainable gas fee is (in NGN).

For example, the gas fee could be more than the intended rentage fee 🙂

May be local underlying blockchain infras would help.

[Andrej Karpathy @karpathy]

It's a bit sad and confusing that LLMs ("Large Language Models") have little to do with language; It's just historical. They are highly general purpose technology for statistical modeling of token streams. A better name would be Autoregressive Transformers or something.

They don't care if the tokens happen to represent little text chunks. It could just as well be little image patches, audio chunks, action choices, molecules, or whatever. If you can reduce your problem to that of modeling token streams (for any arbitrary vocabulary of some set of discrete tokens), you can "throw an LLM at it".

Actually, as the LLM stack becomes more and more mature, we may see a convergence of a large number of problems into this modeling paradigm. That is, the problem is fixed at that of "next token prediction" with an LLM, it's just the usage/meaning of the tokens that changes per domain.

If that is the case, it's also possible that deep learning frameworks (e.g. PyTorch and friends) are way too general for what most problems want to look like over time. What's up with thousands of ops and layers that you can reconfigure arbitrarily if 80% of problems just want to use an LLM?

I don't think this is true but I think it's half true.

[Goody ↑ Startup Builder @goody_dev]

If co-founders aren't replying to your messages now, you arenot alone.

Calmly offer them to leave the team and wait till you get funded, or get to work.

[Goody ↑ Startup Builder @goody_dev]

Setting up web3 projects makes you feel "onchain" already.

[Goody ↑ Startup Builder @goody_dev]

The balance is in loving God above everything.

[Goody ↑ Startup Builder @goody_dev]

@ez0xai Nice stuff. Make it so that you can only post a voice note in your location. It will be useful in war situations.

[shai-hulud @tobiishim]

Update!!!
The pieces get highlighted when you select and then "lerp" across to the destination square, there's move validation and also an ai opponent, I also added little "clack" sounds that play when the pieces hit the board but the audio must be broken .

[Frosty雪 @celestine0x]

Bro I just saw a fucking shooting star

It literally lit up everywhere. Green light dawg

Probably the Omnitrix

If you stay in Ilorin, did you see it?

[Goody ↑ Startup Builder @goody_dev]

@celestine0x Ogbomoso

[Goody ↑ Startup Builder @goody_dev]

Just saw a green meteor or commet or shooting star in Nigeria.

[Lux Capital @Lux_Capital]

We started Lux in 2000 with a simple conviction: the biggest opportunities lie at the frontier of science and technology that others find too hard, too early, or too confusing. Twenty-five years later, that conviction hasn't changed. What has changed is that the world has caught on.

Now compute, automation, and biology have matured into scalable engineering disciplines, and what was once fringe "deep tech" has become essential infrastructure. New talent, new tools, and new industrial capacity now exist to turn the most cutting-edge technology across the physical, computational, and life sciences into enduring businesses.

For these businesses and founders to become category-defining winners, they need meaningful capital and conviction. That is why we are especially excited to announce our largest fund to date, Lux Ventures IX, a $1.5B commitment to investing in the people turning sci-fi into sci-fact.

Today entire sectors of aerospace, biotech, defense, industrials, transportation and beyond are being reinvented by a new generation of brilliantly ambitious, often irreverent, scientists and engineers. And while markets have changed and capital reshapes around fewer companies and larger checks, our focus on the craft remains constant.

That focus matters because science doesn’t scale itself. The path from a result in the lab, only known to a few, to something durable the entire world will use requires a different kind of partnership. One that deploys the first $100K and the last $100M, that stays through the full arc of company-building, that mobilizes a powerful network of kinetic like-minded founders, and that treats capital as a tool rather than the product.

Forty-four people at Lux now manage $7B, still operating with the same discipline and purpose we had on day one. We find and fund founders others have overlooked, back conviction over consensus, and build alongside these rebels of science and tech at every stage.

We’re grateful to our valued LPs who've partnered with us through multiple cycles, and to the founders who trust us with their life's work. The mission continues, with even greater intensity and momentum.

https://t.co/D6emTydcYK

[Roy @im_roy_lee]

the only reason to prioritize X as a founder is if >80% of ur customers are using it

instagram has been responsible for 46% of all new cluely users since months ago and that’s where we’re manly focusing.

VIDEO ALGORITHMS JUST SCALE BETTER

instagram/tiktok are:

> easier to go viral on
> easier to scale working formats on
> teachable (text algos are not)
> consumer can watch the same video format 100x and laugh every time. they can’t for text.
> have WAY more ppl watching, who are all more willing to pay

x is neither learnable nor scalable.

tbh, every single big account has been posting bangers since they started. no one “picked it up” later, they only got better.

if u find a banger format on x, u cannot scale this 100x. post the same banger tweet on 100 diff accounts, and u’ll mostly just flop.

most of u tech ppl are doomed to be ngmi forever on x. ur just not funny or sarcastic or arrogant enough for this place.

ultimately, i only have so much focus in the world.

every tweet i shoot out aura farming random losers in san francisco requires focus that could be spent elsewhere.

FORTUNATELY, i was chosen by God to make it and am one of the rare cases of being BORN gmi.

been >1 year since i started this shit, my rate of growth is unbelievable, i am beyond generational

[Goody ↑ Startup Builder @goody_dev]

@signouthq 🚀

[SignOut™ @signouthq]

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