JuicyTalkAnthropic Releases Claude Fable 5 and Claude Mythos 5: Same Underlying Model, Different Safeguards, New Mythos-Class Tier
Anthropic released two models on June 9, 2026: Claude Fable 5 and Claude Mythos 5. Both belong to a tier called “Mythos-class.” This tier sits above the Opus class in…
Building a Code Dataset Pipeline from NVIDIA Nemotron-Pretraining-Code-v3 Metadata with Streaming, Pandas, and tiktoken
fig, ax = plt.subplots(2, 2, figsize=(14, 9)) lang_counts.head(12).iloc[::-1].plot.barh(ax=ax[0, 0], color=”#76b900″) ax[0, 0].set_title(“Top 12 languages (sample)”); ax[0, 0].set_xlabel(“files”) df[“ext”].value_counts().head(12).iloc[::-1].plot.barh(ax=ax[0, 1], color=”#5b8def”) ax[0, 1].set_title(“Top 12 file extensions (sample)”); ax[0, 1].set_xlabel(“files”) df[“depth”].clip(upper=12).plot.hist(bins=range(0, 14),…
Google Releases Gemini 3.5 Live Translate, a Streaming Speech-to-Speech Audio Model Covering 70+ Languages Across Meet, Translate, and the Live API
Google just announced Gemini 3.5 Live Translate. It is their latest audio model for live speech-to-speech translation. Speech-to-speech means spoken audio goes in, and translated spoken audio comes out. The…
NVIDIA cuTile Python Tutorial: Building Tiled GPU Kernels for Vector Addition, Matrix Addition, and Matrix Multiplication in Colab
print(“\n” + “=” * 90) print(“[5] cuTile kernels are defined only if cuda.tile imports successfully”) print(“=” * 90) if cutile_import_ok: ConstInt = ct.Constant[int] @ct.kernel def cutile_vec_add_direct_kernel(a, b, c, TILE: ConstInt):…
A New Study from Harvard and Perplexity Finds AI Agents Perform 26 Minutes of Autonomous Work per Session vs 33 Seconds for Search
A new working research from Perplexity and Harvard offers field evidence on what AI agents do to knowledge work. It draws on production data from two Perplexity products: Search and…
ClawHub Security Signals: A Coding Guide to End-to-End Security Signal Analysis and Verdict Classification on the AI Skills Dataset
TEXT_COL = “skill_md_content” NUM_COLS = [“skillspector_score”, “static_finding_count”, “skillspector_issue_count”, “virustotal_malicious_count”] TARGET = “clawscan_verdict” def prep(df): out = df.copy() out[TEXT_COL] = out[TEXT_COL].fillna(“”).astype(str).str.slice(0, 6000) for c in NUM_COLS: out[c] = pd.to_numeric(out[c], errors=”coerce”) return…
Xiaomi MiMo and TileRT Push a 1-Trillion-Parameter Model Past 1000 Tokens Per Second on Commodity GPUs
Inference speed is becoming a competitive metric for large language models. Xiaomi’s MiMo team just released MiMo-V2.5-Pro-UltraSpeed, built in collaboration with the TileRT systems group. It decodes faster than 1000…
Microsoft AI Introduces MAI-Transcribe-1.5: 2.4% WER on Artificial Analysis, Best-in-Class FLEURS Accuracy, and Up to 5x Faster Long-Audio Transcription
Last week Microsoft AI has announced MAI-Transcribe-1.5. It is the second iteration of the company’s in-house speech-to-text family. The model targets accuracy across 43 languages, accents, and noisy environments. The…
Google Research Adds Agentic RAG to Gemini Enterprise Agent Platform with a Sufficient Context Agent for multi-hop queries
Google Research team has introduced a new agentic RAG framework. It is built into the Gemini Enterprise Agent Platform. It powers a feature called Cross-Corpus Retrieval, now in public preview.…
Building Reflective Prompt Optimization with GEPA: Multi-Component Prompts, Structured Feedback, and Held-Out Validation
def make_problems(n, seed=0): rng = random.Random(seed) out = [] for _ in range(n): t = rng.choice([“discount”, “travel”, “wallet”, “chain”]) if t == “discount”: unit = rng.choice([40, 60, 80, 120]) qty…
Bullish Backs USD.AI with $100M for AI Infrastructure Loans
JuicyTalk- August 28, 2026
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Simeone’s stance unchanged on wantaway Atletico star Alvarez
- JuicyTalk
- August 28, 2026
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