⏐ Taklimat Pagi
Taklimat Pagi Saya
🔗 baca_penuh: pagi.hejes.my/2026/08/23
> ringkasan_ai
# 🚀 OpenAI & Frontier Models
✅ **GPT-5.6 & ChatGPT Work** [OpenAI] — OpenAI baru lancarkan GPT-5.6 yang lagi bijak dan efisien, sekali dengan 'ChatGPT Work' yang boleh jadi agent untuk settlekan projek long-term merentas apps.💡 **Kenapa Penting** — Model makin power, kerja Master mungkin boleh automate lebih banyak lagi lepas ni.
✅ **Bio Bug Bounty GPT-5.5** [OpenAI] — Program ganjaran untuk cari 'bug' atau risiko keselamatan berkaitan biologi dalam model GPT-5.5.💡 **Kenapa Penting** — OpenAI nak pastikan AI dorang tak disalahguna untuk buat benda bahaya macam senjata biologi.
✅ **Coding Evaluation & Gov Partnerships** [OpenAI] — OpenAI kritik benchmark SWE-Bench Pro sebab tak tepat, dan dalam masa sama kongsi prinsip kerjasama dorang dengan kerajaan/sekuriti nasional.💡 **Kenapa Penting** — Kita kena tahu cara ukur performance AI yang betul, bukan sekadar tengok skor benchmark yang mungkin 'bias'.
# 🧠 AI Research & Reasoning (arXiv)
✅ **Adaptive Reasoning & Long-Horizon Agents** [arXiv] — Kajian pasal AI yang boleh adjust tahap 'berfikir' ikut kesukaran task (Adaptive Reasoning) dan agent yang boleh improve diri sendiri secara *live* masa tengah buat kerja (PILOT in the Loop).💡 **Kenapa Penting** — AI takkan lagi 'overthink' benda senang, dan boleh belajar dari silap secara real-time.
✅ **Formal Theorem Proving & Transformer Fine-Tuning** [arXiv] — Ada teknik baru ProofEvolve untuk pembuktian matematik automatik dan cara fine-tuning Transformer guna 'Frames' supaya lebih jimat memori.💡 **Kenapa Penting** — Ini langkah ke arah AI yang boleh buat penemuan saintifik secara autonomi.
✅ **Multimodal-to-Audio-Video Safety** [arXiv] — Benchmark baru (Multi2AV-Safety) untuk pastikan AI yang generate video/audio dari pelbagai input tak hasilkan content berbahaya.💡 **Kenapa Penting** — Deepfake makin real, jadi safety guardrail macam ni memang wajib ada.
# 🛠️ Infrastructure & Tools
✅ **Granite 4.1 & AWS Foundation Models** [HuggingFace] — Bedah siasat macam mana Granite 4.1 dibina dan panduan training model besar guna AWS.💡 **Kenapa Penting** — Bagus untuk Master kalau nak tahu 'under the hood' macam mana model enterprise dibina.
✅ **vLLM V1 & DeepInfra** [HuggingFace] — Update vLLM V1 yang fokus pada correctness dalam RL, dan integrasi DeepInfra sebagai provider inference di Hugging Face.💡 **Kenapa Penting** — Inference makin laju dan stabil, kos run model mungkin makin murah.
🔥 Top Picks
**GPT-5.6 & ChatGPT Work** (Game changer untuk produktiviti Master!)
**Adaptive Reasoning in Agentic AI** (AI yang tahu bila nak fikir dalam, bila nak jawab cepat).
**PILOT in the Loop** (Agent yang boleh self-correct masa tengah run).
> ls -la berita/
🧠 AI/ML
13Granite 4.1 LLMs: How They’re Built
GPT-5.5 Bio Bug Bounty
Details about the OpenAI Bio Bounty program
ProofEvolve: Neuro-Symbolic Evolution for Formal Automated Theorem Proving
arXiv:2608.26334v1 Announce Type: new Abstract: Automated theorem proving offers a natural foundation for recursive self-improvement in scientific discovery. However, existing neural provers do not fully preserve this recursive structure, where the l
Building Blocks for Foundation Model Training and Inference on AWS
Our approach to government and national security partnerships
Learn how OpenAI approaches government and national security partnerships, with principles for responsible AI use, democratic accountability, and public safety.
Multi2AV-Safety: Benchmarking Safety in Multimodal-to-Audio-Video Generation
arXiv:2608.26535v1 Announce Type: new Abstract: Audio-video generation is rapidly moving from prompt-driven synthesis toward multimodal conditioning, where text, images, audio, and video can jointly shape the generated output. This shift changes the
Don't Overthink, Don't Underthink: Toward Adaptive Reasoning in Agentic AI
arXiv:2608.26442v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have shown that increased inference-time reasoning can improve performance on complex tasks. However, many existing approaches rely on fixed or preallocat
Fine-Tuning of Transformer models with Frames
arXiv:2608.26430v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) strategies such as Low-Rank Adaptation (LoRA) are effective solutions for fine-tuning large-scale pre-trained models; however, their memory requirements scale with
Separating signal from noise in coding evaluations
A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models.
ChatGPT is now a partner for your most ambitious work
ChatGPT Work is an agent that can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.
GPT-5.6: Frontier intelligence that scales with your ambition
More intelligence from every token, stronger performance per dollar, and more capability on demand for your hardest work.
vLLM V0 to V1: Correctness Before Corrections in RL
DeepInfra on Hugging Face Inference Providers 🔥