Afiq Che Man | Influenza season ig

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Afiq Che Man | Influenza season ig

Afiq Che Man | Influenza season ig

@mafqcm

🐍 Data science & machine learning. Studying 日本語. Random stuffs / games / anime off-work. Irregular reply sometimes. MPhil @mjiitofficial @utm_my

Malaysia Katılım Mayıs 2016
529 Takip Edilen1.6K Takipçiler
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Afiq Che Man | Influenza season ig retweetledi
Alexandre Cadrin-Chênevert
Alexandre Cadrin-Chênevert@alexandrecadrin·
@DRARN93 Since 2022, computer vision is lagging after language. In this context, there is no reason why radiologists will be replaced before those who just use a form of language in their job.
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Afiq Che Man | Influenza season ig
got told by my reg apothecary that med costs aren’t climbing so far but am certainly feeling a bit pinch maybe because the usual no name gen drugs aren’t in stock
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Afiq Che Man | Influenza season ig retweetledi
Afiq Che Man | Influenza season ig retweetledi
“paula”
“paula”@paularambles·
they call them crisps there
“paula” tweet media
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OmniReborn
OmniReborn@OmniReborn24·
6-CARD HAND… WHAT COULD GO WRONG?! | Yu-Gi-Oh! Master Duel #yugioh #masterduel
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Andy Smarick
Andy Smarick@smarick·
In 10 years, we'll realize young adults can't read, write, or think as well as they should. We'll wonder how we allowed students to offload huge chunks of their learning to AI. Today we're just watching it happen. This is the most obvious unforced error of our time.
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Joshua Waters
Joshua Waters@TunnelVa·
It's been a while, partner☀️ Playing Phainon has been a joy and a treasure, hard to believe it's been over a year since I began voicing him I am eternally grateful for all of your support, it means more than I could ever express. Keep on journeying starward❤️
Honkai: Star Rail@honkaistarrail

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Neet
Neet@neet_sol·
The reason 9-5 offices are so cold is because you’re surrounded by the ghosts of people’s dead hopes and dreams
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Dovydas Vitkauskas
Dovydas Vitkauskas@Dovydas44444·
In light of massive layoffs at Meta, Microsoft and others, an NVIDIA exec suggests that right now, AI isn’t saving companies money on labor; it’s actually costing them more than the humans they currently employ. Bryan Catanzaro, vice president of applied deep learning at NVIDIA: “For my team, the cost of compute is far beyond the costs of the employees.” So what is the trend, really?
Dovydas Vitkauskas tweet media
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Dmitrii Kovanikov
Dmitrii Kovanikov@ChShersh·
I miss the toxic tech culture of receiving 50+ code review comments. Now everyone just pushes AI slop and doesn’t care as long as CI is green.
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hardmaru
hardmaru@hardmaru·
For years, voice AI has been stuck in a rigid loop: think, then speak. But real human conversation is messy, overlapping, and asynchronous. In our new #ICASSP2026 work, we built a tandem architecture that shifts the paradigm to “speak while thinking.” A fast speech model starts replying instantly, while a backend LLM runs in parallel to inject deep knowledge on the fly. It’s a completely different way to approach conversational AI, making it feel remarkably more alive. Blog: pub.sakana.ai/kame/ 🐢
Sakana AI@SakanaAILabs

We’re excited to introduce KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI, accepted at #ICASSP2026! 🐢 Blog pub.sakana.ai/kame/ Paper arxiv.org/abs/2510.02327 Can a speech AI think deeply without pausing to process? In real conversation, we don’t wait until we’ve fully worked out what we want to say—we start talking, and our thoughts catch up as the sentence unfolds. Fast speech-to-speech models achieve this, but their reasoning tends to stay shallow. Cascaded pipelines that route through a knowledgeable LLM are smarter, but the added latency breaks the flow—they fall back to "think, then speak." In our new paper, we propose a way to break this trade-off. We call it KAME (Turtle in Japanese). A speech-to-speech model handles the fast response loop and starts replying immediately. In parallel, a backend LLM runs asynchronously, generating response candidates that are continuously injected as "oracle" signals in real time. This shifts the AI paradigm from "think, then speak" to "speak while thinking." The backend LLM is completely swappable. You can plug in GPT-4.1, Claude Opus, or Gemini 2.5 Flash depending on the task without changing the frontend. In our experiments, Claude tended to score higher on reasoning, while GPT did better on humanities questions. Try the model yourself here: huggingface.co/SakanaAI/kame

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François Chollet
François Chollet@fchollet·
AI automates tasks, not jobs, and when a task gets cheaper, demand for the job grows. AI cannot automate jobs end-to-end because it lacks autonomy and cannot operate without supervision. There is still zero job from 2022 that can be performed end-to-end by AI, not even translator or customer support associate.
James Pethokoukis ⏩️⤴️@JimPethokoukis

"A decade ago, AI was supposed to replace radiologists. Today, radiologists make more than $500,000 per year, and their employment continues to grow, see chart below. Reading scans is a task, not a job, and when the task gets cheaper, demand for the job grows."

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Jennifer Berkshire
Jennifer Berkshire@BisforBerkshire·
Among the 20K workers Citi is firing: “A.I. Champions and Accelerators” who perform their dayjob while trying to convince their coworkers to adopt AI
Jennifer Berkshire tweet media
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