Dr Joshua Ho

@austin_rief This is like a rich family saying they don’t need any heirs

My friend who works at a large PE firm: "So we just had a firm wide meeting about how we don't need associates anymore"

@grok is one Claude Code product away from me cancelling my Claude Max subscription. I prefer Grok’s real time X access anyways to stay on top of new AI frameworks @elonmusk

@steipete @openclaw What about local models?

Please don't buy a Mac Mini, rather sponsor one of the many contributors of @openclaw You can deploy this on Amazon's Free Tier. #community" target="_blank" rel="nofollow noopener">github.com/clawdbot/clawd…

@coinbase_au @sharonsheah when Elon Musk tweets about dogecoin

We’re giving away an iPhone 17 Pro Max. What notif gets you to tap? → Follow @coinbase_au → Tag a mate and comment what you’d put in the notification One caption + one tagged mate = one entry. Enter as many times as you'd like! We’ll pick the most creative entry.

@theallinpod David's point in 2 prompts

David Friedberg: OpenAI’s rise is the best thing that ever happened to Google “No greater blessing has ever happened to Alphabet than OpenAI's rise.” “Not only did it create the foil for Google in the monopoly sense, but it also took the attention away from Google, focused it on OpenAI, and that attention fundamentally damaged OpenAI's strategic product capabilities because they had to start to be so much more careful about what they said and how they said it.” “And the opposite was happening at Google at the same time, which is Larry, Sergey and Sundar being given permission by the board to take risks, to go hard, to figure this out. And boom! It's amazing how the horse race has changed.” “The reason Google didn't lean into AI for years, even though they had the technology, is because they were nervous about cannibalization to search, they were nervous about the quality of the product, they didn't want to release things too early, and then they changed their posture.” “Which, by the way, I would argue is the opposite at OpenAI in the last couple months.” “I used to use advanced voice on ChatGPT all the time. I cannot stand it anymore. I do not use it.” “It has basically hedged away all of the value because it tries to be polite, it tries to make sure that it's giving you warnings all the time.” “It doesn't want to give you data because it's scared that it might give you the wrong data.” “OpenAI has been acting like an incumbent fearful of losing market share and fearful of getting attacked in the media and attacked by consumers for saying the wrong thing.” “And so they've taken this kind of defensive posture that I think has fundamentally damaged the product and the brand.”

@OfficialLoganK @GoogleAIStudio Hi 👋🏼 yes please

Big upgrade to vibe coding in @GoogleAIStudio lands in Jan, but if you want to test early… 👇🏻

Google just accidentally revealed how its AI search systems actually work. In the process, they validated what SEO Stuff (seo-stuff.com) has been doing all year to get customers more traffic + sales from Google's traditional search and AI platforms. Now that none of it is a secret, let's talk about it. But before we get into it… If you want free cheat codes for getting inside ChatGPT, Gemini, Perplexity, and Google AI Mode within the next 30 days, just RT this, follow me, and reply “AI SEO Cheat Codes.” I’ll DM them to you. You must do all 3 for the DM. Alright, let's jump into it. Metehan Yesilyurt, who previously went viral when he expertly analyzed Perplexity's ranking factors, recently broke down Google AI ranking factors in a blog post. (Link in the replies.) It was fascinating. Basically, as noted by Yesilyurt, by selling the underlying infrastructure through a product called Google Cloud Discovery Engine (Vertex AI Search), Google revealed a lot about its AI systems work. If you understand what Discovery Engine exposes, you understand how Google AI Mode, AI Overviews, and future AI search features are likely ranking and retrieving your content. I'll talk about the 7 ranking signals below, but I advise you to read the entire blog post I'm linking to because it goes into way more helpful technical detail: 1. Base Ranking The core algorithm’s initial relevance score. 2. Gecko Score (Embedding Similarity) Vector similarity between your content and the query. Semantic match. 3. Jetstream (Cross-Attention Relevance) A more advanced model that understands negation, contrast, context, and nuance better than embeddings. 4. BM25 Keyword Matching Kind of self-explanatory. Yes, keyword matching still matters. 5. PCTR (Predicted Click-Through Rate) A three-tier prediction model: Tier 1: Popularity Tier 2: PCTR Tier 3: Personalized PCTR (unlocked only after 100,000+ queries) 6. Freshness Time-sensitive recency scoring. 7. Boost / Bury Rules Manual ranking adjustments based on business logic. This is the most transparent look we’ve ever had into Google’s AI ranking pipeline. Discovery Engine also exposes the retrieval pipeline: Max chunk size: 500 tokens (~375 words) Optional: ancestor headings travel with each chunk Tables and images get parsed Layout parser + Gemini-enhanced understanding (LLM-augmented indexing) This means: every important point needs to live inside a 500-token block with clean headings and clear structure. If your content is one massive wall of text, you're done. Also, I hate to be the "I told you so" guy on this, but schema matters. For some reason it has become controversial to say this on social media, but it was obvious and now it is confirmed. Discovery Engine shows Google processes structured data with three separate flags: Searchable (affects recall) Indexable (affects filtering + ordering) Retrievable (affects what the model can output) These are independent. Meaning: A field can influence ranking without being visible, or be visible without influencing ranking. A massive hint at how Google uses structured data for AI Mode. Also, Google revealed the 4-stage AI search pipeline 1. Prepare Query understanding, synonym mapping (time-aware), autocomplete, NLU. 2. Retrieve Chunking, layout parsing, schema extraction, embeddings. 3. Signal The 7 signals above. 4. Serve Gemini 2.5 Flash generates the final answer, applies instructions, safety filters, related questions, and grounding rules. Traditional Search to AI Overviews to AI Mode are simply different configurations of this same pipeline. So what does all this mean? Well, it means you must optimize for three layers at once: Layer 1: Semantic similarity (Gecko) Your content needs to clearly match the intent of the prompts you want. Layer 2: Cross-attention relevance (Jetstream) Jetstream rewards: clear definitions direct answers contrast statements “X vs Y” “Best for ___” “Without ___” Layer 3: Chunk-level clarity Your content must be extractable in 500-token blocks with: question-based headings two to three sentence answers TLDR summaries clean HTML factual claims lists and comparisons This is exactly what AI systems quote. And this is exactly why SEO Stuff (seo-stuff.com) works so well in AI search. The Discovery Engine findings validate the entire SEO Stuff approach from long before this documentation was public. Let me break down the packages through the lens of Google’s architecture: SEO Stuff Gold Plan seo-stuff.com/gold-plan-pack… 10 long-form, comparison-based, extractable articles Structured in 500-token blocks Question H2s Two to three sentence direct answers TLDR blocks FAQ schema + product schema 3 DR50+ backlinks to strengthen entity signals Gold Plan maps to: Gecko (semantic match) Jetstream (cross-attention relevance) BM25 (keyword match) Freshness Entity trust (for Boost/Bury) This is the fastest path to appearing in ChatGPT, Gemini, Perplexity, and Google AI Mode. SEO Stuff Premium Content Bundle seo-stuff.com/premium-conten… 60 comparison-driven articles Structured to match the exact pattern LLMs extract Category-defining content Builds topical coverage + entity clarity Creates a deep corpus for Jetstream + embeddings Premium Bundle maps to: Retrieval depth Structured chunking Ancestor heading clarity Embedding similarity AI model grounding This is how you train AI systems to associate your brand with your category. SEO Stuff Premium Backlink Bundle seo-stuff.com/premium-backli… 3 DR50+ backlinks from domains LLMs already trust Reinforces brand consistency across the web Boosts entity recognition Backlinks help with: Base ranking PCTR (popularity + trust) Boost/Bury eligibility Entity clarity This is why so many customers reorder. It works. Google is not hiding its AI search architecture. They literally exposed: The signals The ranking layers The chunk sizes The parsing logic The semantic models The engagement tiers The answer generation flow The brands that understand this and structure their content accordingly will run through the next era of search like absolute beasts. And SEO Stuff (seo-stuff.com) was built specifically to map to this architecture. If AI is replacing the first click, your content must replace the first impression. Plain and simple. If you want cheat codes for getting inside ChatGPT, Gemini, Perplexity, and Google AI Mode within 30 days… RT this, follow me, and reply “AI SEO Cheat Codes.” You must do all 3 for the DM.

@DiscussingFilm Hard disagree. Best is > Kevin is now old on old folk’s home > kids take him back for Christmas holiday > leaves him at holiday home in a foreign country > Kevin defends his house again

Macaulay Culkin says he has an idea for a ‘HOME ALONE’ legacy sequel: “I’m either a widower or a divorcee. I’m raising a kid…. I’m not really paying enough attention & the kid is kind of getting miffed at me & then I get locked out. My son won’t let me in… and he’s the one setting traps for me. The house is some sort of metaphor for our relationship” (Source: variety.com/2025/film/news…)

I remember when I first heard of the 18 Harvard kid year old confirms Facebook once did he know how to figure out Thiel and internet, advertising was the same again but never. Well done, Mark

@AnthropicAI If Claude code is good enough for the Chinese, consider me sold. Just subscribed.

We disrupted a highly sophisticated AI-led espionage campaign. The attack targeted large tech companies, financial institutions, chemical manufacturing companies, and government agencies. We assess with high confidence that the threat actor was a Chinese state-sponsored group.

@AlexTheGoodman @levelsio Why would he want your left nut 😂 Sounds like a lose-lose to me

@levelsio bro i literally do not believe the product fulfills this ad at all. but if i am wrong then i will give you my left nut

World Labs is now live for everyone! Try it and make any image into a 3d world you can walk around in Already on Interior AI for awhile and used by many people to get a better idea of their interior redesigns image2world is just the first step, their end game is fully realistic world models

@bballforever_ Neighbours thought that Wood had Ja Morant over for dinner that night

Former Lakers player Christian Wood fired several rounds during an attempted home invasion in Sherman Oaks on Wednesday at 1pm. Wood confronted the burglars before running outside and firing 3-4 rounds at the ground, police said. The suspects were scared off and fled. No one was injured.

@aryanlabde So someone who can build anything and someone who can sell anything. I’d hire the one who can sell anything

You’re a solo founder. You can only hire one: – Killer marketer – Rockstar engineer Who gets the job?

@sweatystartup The secret toilet on the 7th floor of law building is the best place to take a dump

I'm talking to a class of 300 students in about an hour. What is one thing you wish somebody would have told you before you graduated?

@Route2FI ICO days

When was the last time you really felt crypto was in easy mode?

My goal in life is to be someone who people address as ‘big dog’

@mikefutia Bananananananan

Nano Banana + n8n is legitimately insane 🤯 Google's Nano Banana creates studio-quality static ads. But manually generating variations one-by-one takes forever. This n8n automation generates 1,000+ ad variations in minutes. Fully automated. Perfect for DTC brands & media buyers who need fresh creative for testing without hiring designers. Here's the problem: You need 50+ ad variations to test angles, but Nano Banana only outputs one image at a time. Manually uploading and tweaking prompts for each variation kills hours. This n8n automation solves it: → Upload ONE product image via n8n form → OpenAI Vision analyzes your product automatically → AI generates custom image prompts (you choose quantity: 50, 100, 1000+) → Nano Banana creates static ad images in bulk → All images auto-stored in Box for instant access No manual prompting. No designer bottlenecks. No waiting on agencies. What you get: → Hundreds of unique ad variations from one upload → Different angles, backgrounds, compositions → Production-ready static ads → Perfect for testing creative on Meta/TikTok Built 100% in n8n. Want the complete n8n template? > Comment "BANANA" > Like this post And I'll send it over (must be following so I can DM)

@elonmusk Doing what I can for the future of humanity

Please take a moment to vote your Tesla stock. It is super important. Control of Tesla could affect the future of civilization.

I made it and lost it all due to the Luna crash But cashing out along the way helped me paid for a car, a diploma and contribute to a house

@SamuelBeek Most generalisable problem, as everyone loves to travel hence applicable to anyone of any age

Travel planning isnt that big of a problem, why does it keep surfacing in AI ads?