stulab

waduh haussr

[Mradul @driftauz]

Data Analyst and PowerBI Developer after this launch..

[stulab @_pnajic]

@zharki2018 Bang buat kulkas prefer merk LG di budget 5 jutaan melar ada apa aja ya? Kalau yang non merk LG ada nggak sih yang bagus?

[Dedy Ong @MrOngDedy]

Rekatin power track ke dinding keramik pake "GRH SA200". Hasil liatin teknisi kerja kemaren sore. 😂

Akhirnya minta dikit sealant-nya buat tempel colokan ke dinding.

Dari kemaren tuh lepas mulu. Udah pake double tape 3M yang katanya strong banget bisa nahan 6,7kg juga tetep lepas. 😂

Semoga yang ini awet deh.

Dipercaya oleh Teknisi yang masang frame aluminium ke plafon. Logikanya pasti strong banget. 🫡

[Andrew Ng @AndrewYNg]

New: A map of the most important skills in AI Engineering. https://t.co/VVkn1Dqp1N

[Founder Thoughts & Strategies @mogulinfluence]

This masterclass literally shows entrepreneurs how to use game theory to maximize profit with minimum effort:

[RetroChainer @RetroChainer]

https://t.co/eYFjvCZH0s

[zay @overclocked_cat]

Laptop Buying Guide V.2 is released! Buat yang mau nyari laptop untuk keperluan kuliah tapi bingung mau beli laptop apa yang worth it, bisa liat guide yang aku bikin ini ya, selain ada list laptop, ada juga tutorial lain kyk instalasi Windows dll!

https://t.co/YJf8mZEVJ8

[divyansh tiwari @DivyanshT91162]

This is insane.🤯

Someone built an AI assistant framework that does almost everything.

AstrBot (37k+ GitHub stars)

Deploy it to:

→ Telegram
→ WeChat
→ QQ
→ Feishu
→ DingTalk
→ And more

You get:

• Multi-model support
• AI Agents
• Built-in RAG
• 1000+ plugins
• Secure code execution
• AI personalities
• Proactive conversations

Perfect for building:

• 24/7 AI assistants
• AI customer support
• Team copilots
• Community bots
• Workflow automation

Docker. One command.

100% open source.

Repo👇

[Ridwan Gunawan @RidwanRWG]

Beberapa hari ini, bersliweran orang mau belajar financial model (FM). Daripada belajar di FMVA - CFI, saya lebih merekomendasikan https://t.co/kxirDXTuXx buat belajar FM gratisan.

Pengajarnya ini selain alumni EYP, jg CFA, top dah orangnya.

[Shann³ @shannholmberg]

what's the difference between a loop and a graph? (marketing edition)

both are ways to run an agent, the difference is who decides the path, the agent or you.

a loop still starts with you. you set the goal, the brief, and the bar it has to clear. what the agent owns is the path.

take writing an SEO article: hand it the brief and it drafts, reads the draft back against that brief, rewrites the weak parts, checks again, and keeps circling until it clears the bar. the one thing you did not write is the step-by-step it took to get there.

a graph is you drawing the steps and the routes between them ahead of time. same article, but now you set the map: research the keyword and the competitors ranking for it. draft from what you find. score that draft against your rubric.

if it clears, add the internal links and publish. if it misses, back to the draft. the agent still decides how to handle each step, it just travels the routes you laid down.

the shape of this has a name, a state machine. every node is a state the work can be in, and a check at each one decides where it goes next, forward when it clears or back to an earlier node when it misses.

if you have built a workflow in n8n, you have already drawn one. nodes wired together, branches that fire on a condition, a step that loops until it clears, that picture is a graph. an agent graph is the same shape, the nodes hold agents doing the work instead of single api calls.

the way I think about it, a graph is a map of loops and checkpoints. some nodes run once, others are their own loop where the agent works something out, and the checkpoints between them read the result and route the work. you keep laying down nodes and checkpoints until the map reliably gives you the output you want.

the vault accelerator I run at my agency is one of these maps, 3 sessions that hand off in a fixed order:

> research session: reads our company brain and past campaign results, pulls in competitor and market context, and builds the cohort we go after
> landing page session: takes that research and builds the page from it
> content session: uses the research and the page to write the copy, illustrations, and slides for the live sessions we run

inside the content session runs a loop, a critic scores each draft against a rubric and sends it back until it clears the bar. that is one node on the map, the checkpoints between the sessions carry the work from one to the next

a graph earns its extra setup on anything you run every week:

> validation gates the work cannot skip
> a fixed set of routes the job can take
> a clear failure point, you see the exact step something broke on

a loop on its own is enough for the work you only do once, where you don't know the path yet, let the agent find it. graphs earn their place on the jobs you repeat, the content pipeline, the SEO and AEO funnel step by step, the vault accelerator

once the map works you reuse it, feed it the next cohort and the whole pipeline runs again

past the loop, the next thing you design is the map it runs inside.

[darkzodchi @zodchiii]

EVERYONE WANTS TO TRY KIMI K3. NOBODY WANTS TO CHANGE THEIR SETUP. KIMI GAVE THE SOLUTION.

Moonshot now sponsors claude-code-router: your terminal, your hooks, your CLAUDE.md, their 2.8 trillion parameters.

35,000 stars. And the Kimi part is one click:

→ built-in Kimi presets: import the API or a Kimi Code subscription in one click

→ subscription requests pass through natively, zero protocol conversion

→ your Kimi balance and usage show up right in the router's dashboard

→ automatic failover when a provider goes down mid-session

→ K3's cache pricing does the rest: repeated context at $0.30 per million

One honest note: the router's proxy mode installs a root certificate, so skip that toggle unless you know why you need it.

The default setup doesn't touch it.

Grab it 👇

[George Ferman @Helios_Movement]

If you don't have time, money or whatever excuse you use in order not to look into these tools, then just stretch once in the morning and once in the evening.

That's it.
It's free and can be done within 5 minutes (if you have time to be on socials, you have 5 minutes to stretch).

When animals in the wild experience a traumatic event, they pass through their freeze response by trembling.

In one study for example where mice were deliberately traumatized, half of the mice were allowed to tremor naturally after the trauma and the other half were prevented from trembling.

It was discovered that the mice that were not allowed to successfully go through their natural tremoring process had reduced resiliency to subsequent life-threatening experiences.

This brings us to TREs.

Trauma-releasing exercises (TREs) were designed to engage the primitive mammalian survival mechanism used to recover from a traumatic event.

The same tremors found in other mammalian species can also be easily evoked in the human species through a series of five simple exercises.

The exercises produce a slight fatigue in the major muscle groups of the legs and pelvis.

This is done by isolating the muscle groups and exercising them individually (tap in the pic).

Disclaimer: Consult your therapist, psychiatrist etc before using these.

[Clair 光 @lynxluna]

Tukang reparasi skrg udah sampai level micro-soldering dan flashing ROM. Memang belum sampai bikin produk baru.

Bayangin kalo industrialisasi jalan, yang gini-gini bisa dikembangkan untuk produk baru.

Dulu bgt juga pernah rekrut kang reparasi hape pas bikin startup hardware.

[Gogo | Dota for Toxicity @lwastuargo]

Calling a prediction for the evolution of Agentic AI Engineering

☠️ Prompt Engineering
☠️ Context Engineering
☠️ Harness Engineering
☠️ Loop Engineering
📈 Designing Data-Intensive Agents

Cuz building good agents is just software engineering all over again

[Mustafa. @oprydai]

almost every engineering system is signal in, signal out.

• audio
• radar
• images
• sensors
• motors
• circuits
• control systems

all of them process information over time.

signals and systems by alan v. oppenheim is one of the books that teaches you how to see that structure.
a signal is not just data.

it is behavior across time, space, or frequency.
a system takes that signal and transforms it.

• filtering noise
• amplifying patterns
• extracting features
• predicting behavior
• controlling response

once you understand convolution, Fourier transforms, sampling, and frequency response,
the world starts looking different.

• sound becomes waves.
• images become frequencies.
• sensors become streams.
• machines become transformations.

engineering becomes the art of shaping signals.

[Master Metabolism @lowmegatron]

Taurine ameliorates insulin resistance and beta cell dysfunction while reducing lipid peroxidation byproducts, including 4-HNE, a driver of Alzheimer’s, cancer, and liver damage.

1 g taurine, 3x/day for 2 weeks.

The research was conducted in non-diabetic obese men given IV lipids (fats) to simulate chronically elevated free fatty acids, a feature of human obesity and type 2 diabetes, in which adipose lipolysis keeps circulating free fatty acids elevated.

“Oral administration of taurine ameliorated lipid induced impairment in insulin sensitivity and beta cell function in non-diabetic men who were either overweight or obese. This study suggests, but does not provide definitive proof, that the beneficial effect of tuarine was mediated by its antioxidant activity, and we acknowledge that mechanisms independent of oxidative stress cannot be ruled out.”

Ref: Oral taurine but not N-acetylcysteine ameliorates NEFA-induced impairment in insulin sensitivity and beta cell function in obese and overweight, non-diabetic men

[Roy Carrilho @RuiCarrilho5]

ended up finding this book on the matter. it's apparently a more academic, practical version of DDIA.

and it's free!

[Kirk Borne @KirkDBorne]

“Agentic Design Patters Hands-on Guide” = 472 pages of “practical advice designed to help developers master the art of building sophisticated AI agents. As artificial intelligence evolves from simple reactive programs to autonomous entities capable of understanding context and making complex decisions, this book provides the essential Design Patterns and proven techniques needed to construct intelligent systems effectively. Each of the 21 Design Patterns represents a fundamental building block for creating agents that can perceive their environment, make informed decisions, and execute actions autonomously.”

[Math Cafe @Riazi_Cafe_en]

MIT's "Street Fighting Mathematics"

This course teaches the art of guessing results and solving problems without doing a proof or an exact calculation.

Book: https://t.co/n8o2YlrT7Q

[Sebastian Raschka @rasbt]

After 18 months of writing, coding, and experimenting, Build a Reasoning Model (From Scratch) is
finally out!

My first copies just arrived! 📚

440 full-color pages. Inference scaling, reinforcement learning, and distillation from scratch.