Kisii Tech Hub

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Kisii Tech Hub

Kisii Tech Hub

@KisiiTechHub

🌟 Welcome to Kisii Tech Hub! 🌟 Bringing together technology enthusiasts, service providers, and developers to foster innovation, collaboration, and growth.

Kisii Katılım Haziran 2024
112 Takip Edilen10 Takipçiler
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Noisy
Noisy@noisyb0y1·
20 year old American student invented hand tracking technology for $3 and built it in one evening. Bought an infrared diode and a photoresistor. Soldered wires to a microcontroller the size of a coin. Connected it to an old laptop. 0:11 seconds perfectly shows the diodes and hands working. The principle is simple - the diode sends infrared light, the photoresistor registers how it reflects off skin. Claude Code converts this data into joint coordinates in real time. It worked. The system drew a green skeleton on every finger - 21 tracking points accurate to the millimeter. No special equipment, just your hands and diodes. Shot 14 seconds in the bathroom and posted it on Twitter. A week later a major tech company reached out. They had been developing an AR headset and looking for a hand tracking system for two years. Spent millions on R&D and didn't get what he built in one evening. Offered $230,000 for the technology. The next day the company was already testing the young genius's new product.
Defileo🔮@defileo

x.com/i/article/2045…

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Vaibhav Sisinty
Vaibhav Sisinty@VaibhavSisinty·
Did xAI just mass-murder the entire voice AI industry? 🤯 Grok just launched two voice APIs. Speech-to-Text and Text-to-Speech. Built on the same stack powering Tesla cars and Starlink support. And priced at 10x cheaper than ElevenLabs. Speech-to-Text: $0.10/hr batch. $0.20/hr streaming. Text-to-Speech: $4.20 per million characters. 25+ languages. Real-time streaming. Speaker diarization. Already outperforming ElevenLabs, Deepgram, and AssemblyAI on word error rate. TTS ships with expressive tags like [laugh], [sigh], , . Voices that don't sound like robots reading a script. ElevenLabs spent years building a voice AI company. xAI built voice AI for cars and satellites.
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Ronin
Ronin@DeRonin_·
This 2-hour Andrej Karpathy lecture will teach you how to build a Neural Network from scratch better than most engineers at top AI companies will ever bother to learn No frameworks. No libraries. Just pure code and math The same guy who built Tesla's Autopilot AI and co-founded OpenAI recorded this for FREE on YouTube Bookmark & give 2 hours, no matter what. It'll be the most productive thing you do this week
vixhaℓ@TheVixhal

x.com/i/article/2044…

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Viktor Oddy
Viktor Oddy@viktoroddy·
❤️‍🔥 Just Recorded a 16 min Tutorial on How to use Gemini 3.1 + Seedance 2.0 Build Cinematic $10k Websites (step-by-step) You can now build stunning marketing sites fully with AI
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Claude
Claude@claudeai·
Introducing Claude Design by Anthropic Labs: make prototypes, slides, and one-pagers by talking to Claude. Powered by Claude Opus 4.7, our most capable vision model. Available in research preview on the Pro, Max, Team, and Enterprise plans, rolling out throughout the day.
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Ayaan 🐧
Ayaan 🐧@twtayaan·
Linux user connecting to wifi
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chiky handler
chiky handler@chiky_handlr·
Who made this?? 🤣
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Elon Musk
Elon Musk@elonmusk·
Congrats to the @Tesla_AI chip design team on taping out AI5! AI6, Dojo3 & other exciting chips in work.
Elon Musk tweet media
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RossRadio
RossRadio@cqcqcqdx·
PCB milling
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Emmanuel
Emmanuel@ez0xai·
i built jarvis to FaceVerify - real-time hand tracking - virtual cursor - pinch to click - draggable panels controlled entirely with your webcam MediaPipe + Next.js try it: faceverify-app.vercel.app/jarvis works best on desktop
Emmanuel@ez0xai

saw someone tweet about how Opay does visual KYC verification so i built FaceVerify uses MediaPipe Face Landmarker for live face checks in the browser. live demo: faceverify-app.vercel.app open source: github.com/emmanueltaiwo/…

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Tuki
Tuki@TukiFromKL·
🚨 Andrej Karpathy just explained the scariest thing happening in software right now.. someone poisoned a Python package that gets 97 million downloads a month.. and a simple pip install was enough to steal everything on your machine.. SSH keys.. AWS credentials.. crypto wallets.. database passwords.. git credentials.. shell history.. SSL private keys.. everything.. and here's the part that should terrify every developer alive.. the attack was only discovered because the attacker wrote sloppy code.. the malware used so much RAM that it crashed someone's computer.. if the attacker had been better at coding.. nobody would have noticed for weeks.. one developer.. using Cursor with an MCP plugin.. had litellm pulled in as a dependency they didn't even know about.. their machine crashed.. and that crash saved thousands of companies from getting their entire infrastructure stolen.. Karpathy's take is the real wake up call.. every time you install any package you're trusting every single dependency in its tree.. and any one of them could be poisoned.. vibe coding saved us this time.. the attacker vibe coded the attack and it was too sloppy to work quietly.. next time they won't make that mistake.
Andrej Karpathy@karpathy

Software horror: litellm PyPI supply chain attack. Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords. LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm. Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery - Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks. Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages. Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible.

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Mario Nawfal
Mario Nawfal@MarioNawfal·
🇮🇷🇮🇱 Why Iran chose cluster bombs over conventional warheads Simple math. Israel's Arrow system is built to kill one big warhead. So Iran sends one missile that splits into 80 bomblets at 23,000 feet. That single radar track suddenly becomes dozens of small falling objects scattering across six miles, and no air defense system on earth can chase them all. Over 100 countries banned these weapons because of what they do to civilians. Iran, the U.S., and Israel never signed. Now Israeli neighborhoods are learning why. Source: AI Telly
Mario Nawfal@MarioNawfal

🇮🇷🇮🇶Tiny Iranian FPV kamikaze drones reportedly breached U.S. bases in Iraq, slipping past advanced air defenses in low-level attacks launched by Iran-backed militias. Source: @ArmedExplained

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Papavin
Papavin@mumiasfinest·
Is this practical? How safe is it? Mechanics in the house.
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Kisii Tech Hub@KisiiTechHub·
Julian Derry@CyberSamuraiDev

A Deep Dive into Mobile Forensics I recently completed a full mobile forensic analysis on an iPhone 13 Pro and it was a powerful reminder of how much a device actually remembers. This was an advanced logical extraction with verified image integrity. Even without diving into content, the metadata alone told a story. From location artifacts, I reconstructed where the device had been, the routes it traveled and the exact timestamps tied to those movements. But more importantly, I could see how those locations were generated. Some coordinates were tied to ride activity such as uber and bolt. Others came from navigation searches. Some were linked to shared live locations inside messaging apps. Each source leaves a different footprint. A searched address tells a different story than an active trip. A shared live location suggests intentional disclosure. The coordinates are only part of it, the behavior behind them is the real evidence. The “most visited locations” view made patterns obvious. Certain coordinates appeared repeatedly, building a clear picture of routine and frequency over time. On the communication side, interaction volume alone highlighted the primary contacts. Without even reading conversations, it was immediately clear who the highest frequency messaging relationships were. Volume builds pattern. Pattern builds context. Call analysis went just as deep. Even when call entries were deleted, I could still determine whether interactions were audio or video, which platform they occurred on, how long they lasted, and whether they were answered, missed or rejected. Deleting a visible log doesn’t erase the underlying artifacts. I was also able to recover delivered media, expired content, deleted messages and metadata tying everything to specific timestamps and user actions. Here’s what stands out. Phones don’t just store content. They store behavior. They store routine. They store intent. Files can be deleted. Logs can be cleared. But the artifacts remain. #digitalforensics #DFI #mobileforensics #cybersecurity

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