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- Kimi K2 Beats GPT-5 & Sonnet
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Welcome to another edition of AI PlanetX.
Chinese Kimi K2 beats GPT-5 and Claude; XPeng cuts robot’s leg to prove it’s not human; Altman says AI may soon run companies.
Inside This Edition: 💎
Hottest AI News
Top AI & SaaS Tools
AI Tutorial: Prepare for Any Job Interview
Top AI & Tech News
AI Art Spotlight
Resource of the Day: Hugging Face’s Masterclass on Training LLMs
AI Video Tutorial
Launch Your Newsletter & Make $20K/Month
Hottest AI News
Moonshot
Chinese Kimi K2 Model Beats Both GPT-5 and Claude Sonnet
The AI landscape just shifted dramatically. Chinese startup Moonshot AI has released Kimi K2 Thinking, an open-source model that's outperforming OpenAI's GPT-5 and Anthropic's Claude Sonnet 4.5 across key benchmarks.
Details:
Kimi K2 Thinking hit record-breaking results — 60.2% on BrowseComp (vs GPT-5’s 54.9%), 71.3% on SWE-Bench Verified, and 44.9% on Humanity’s Last Exam. It surpassed MiniMax-M2 to become the top open-source model. The trillion-parameter system can perform 200–300 sequential tool calls with transparent reasoning
It's released under a Modified MIT License, enabling complete commercial use. The sole requirement: if your product serves over 100M users or earns $20M+ per month, you must display "Kimi K2" in your interface
Its standout feature is explicit reasoning traces with agentic tool use, powering autonomous workflows like automated reporting. Advanced quantization doubles speed without accuracy loss, and the 256k context window supports long reasoning sessions
This release shows AI progress has become truly collaborative—the leading reasoning model isn’t a closed product but open and available to all.
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XPeng
XPeng Cuts Robot's Leg to Prove It's Not Human After Social Media Refuses to Believe
XPeng's latest humanoid robot IRON has sparked massive online debate after appearing so lifelike that viewers refused to believe it was actually a robot, forcing the company to take dramatic measures to prove its authenticity.
Details:
When IRON walked the stage with human-like grace, many thought it was fake. CEO He Xiaopeng released footage showing its internal parts, but doubts persisted. Finally, XPeng cut IRON’s leg live on stage to prove it was real
The reveal sent XPeng’s shares up nearly 9% to HK$89.4. The 1.7-meter robot runs on solid-state batteries and three Turing chips, with 82 degrees of freedom and lifelike flexible skin. XPeng will use automotive-grade manufacturing and release a global SDK for developers
He sees robotics as XPeng’s next big leap—potentially a $20-trillion market. Alongside IRON, XPeng showed vision-language-action models, a 2026 Robotaxi fleet, and its first flying car. Mass production begins in 2026 for commercial use
IRON’s lifelike design marks a turning point in robotics—machines appear so real that proving they’re not human means exposing their inner parts.
Top AI & SaaS Tools
Dialora (Life-time Deal): AI voice agents that answer calls, qualify leads, call back promptly, and book appointments using your business-trained, on-brand responses
Postiz: Social media AI agent that schedules your posts across 20+ channels and supports MCP, letting you connect to anything [F-R-E-E Trial]
OlmoEarth: Analyzes satellite imagery to answer key environmental questions—like spotting illegal mining, predicting harmful algal blooms, or mapping flood risk
Fusion 1.0: First AI agent that unifies product, design, and code by connecting Slack, Jira, Figma, and your repo to turn ideas into production features [F-R-E-E]
Google Whisk: Create and remix images by dragging and dropping photos as subject, scene, and style inputs, available in 77 countries [F-R-E-E]
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AI Tutorial
How to Use NotebookLM to Prepare for Any Job Interview
Tired of spending hours googling company info and guessing what interview questions you’ll face? NotebookLM can handle everything — research, organize, and even coach you through mock interviews automatically.
Create Interview Notebook
Go to NotebookLM and press Create New. Name it something specific, like “Tesla Product Manager Interview Prep.” Then tap on Discover Sources and enter a prompt such as:
“I’m preparing for a Product Manager interview at Tesla. Find sources with company details, recent projects, and interview insights.”Configure Coaching Style
Press Settings → select Custom Style.
Set up your preferences:
Style/Voice: “Act as a professional interview coach who challenges and motivates.”
Goal: “Help me ace the Product Manager interview at Tesla by giving realistic feedback.”
Research Role and Company
Ask NotebookLM:
“What are the latest updates about Tesla’s product strategy?”
Follow up with:
“What key skills does Tesla value in Product Managers?”
Tap Save to Note to keep the best summaries for later review.
Generate Practice Questions
Ask: “Give me 10 behavioral and 10 technical questions for a Product Manager role.”
Then press Save to Note → three dots → Convert to Source.
These questions will become part of your training material for mock interviews.
Break Down Model Answers
For each saved question, ask NotebookLM:
“Give a structured sample answer using the STAR method.”
Then review how it breaks down:
Situation: What was the context?
Task: What needed to be achieved?
Action: What steps were taken?
Result: What was the measurable outcome?
Save the best ones and rephrase in your own tone.
Create Personalized Interview Video Guide
Tap on the pencil icon on Video Overview.
Change the focus to something like:
“How to handle product sense and behavioral questions for Tesla interviews.”
Then press Generate to receive a personalized training video script.
You can even regenerate with a different style (e.g., “Friendly mentor” vs “Tough coach”) to compare tone.
Build Practice Routine
Use your saved questions and STAR answers to simulate interviews:
Read each question aloud, record your response.
Compare your delivery with NotebookLM’s feedback or generated answers.
Note down improvement areas in your notebook.
Repeat twice a week until you feel confident.
Review and Refine
Before your real interview:
Ask: “Summarize my progress and weak areas.”
Generate a final checklist with:
• Topics I’ve mastered
• Areas I should revisit
• Mock sessions completed
Print this for your final review.
Note: Record your mock answers and ask NotebookLM to summarize tone, clarity, and confidence levels. This mimics real coaching sessions.
Top AI & Tech News
Microsoft’s Mustafa Suleyman launched the MAI Superintelligence Team to build targeted systems in medicine and energy over open-ended AGI
Sam Altman says OpenAI could have an AI CEO, with most departments run primarily by AI within a few years
Perplexity upgraded its Comet AI with better web interaction, multi-tab support, and improved performance
Seven lawsuits claim ChatGPT caused harm and distress, including four deaths, leading OpenAI to add parental controls and better distress detection
AI Art Spotlight
Create Your Own Photo Like This Using the Prompt Below:
A dynamic 8K photograph, combining hyperrealism with a high-fashion editorial aesthetic, presents a male figure (upload face as reference) against a graffiti-covered brick wall in a gritty yet stylized urban alley. The mood is powerful, artistic, and exudes raw, energetic youthfulness. Dramatic, directional street lighting from above casts strong shadows, emphasizing his strong jawline and the sculptural quality of his sharp assassin-style outfit, creating a modern chiaroscuro effect. Shot on an 85mm f/1.8 lens, a full-body shot positions him slightly off-center in a striking, almost defiant pose, one hand casually in his pocket, radiating an undeniable presence. He embodies minimalist, tactical elegance — wearing a perfectly fitted dark tailored suit with subtle carbon-fiber paneling, a high-neck performance shirt, and sleek, minimalist combat boots. The intricate details of the graffiti, the texture of the brickwork, and the subtle sheen of his suit are rendered with astonishing clarity. The visual style is overwhelmingly photorealistic, almost indistinguishable from a high-quality photograph, with a bold, graphic composition and vibrant yet desaturated urban tones.Model: Gemini 2.5 Flash Image (Nano Banana)
Resource of the Day
A 214-Page Guide to Training LLMs, from Hugging Face
This 214-page guide from Hugging Face is a practical, end-to-end playbook for training modern LLMs. It walks you through the full pipeline—pre-training, mid-training, and post-training—covering tokenizer choices, attention variants, positional encodings, stability tricks, sparse/MoE scaling, and long-context methods.
The core message is clear: data curation drives real quality, so it includes concrete recipes, curriculum strategies, and ablation tactics.
