Channel
@StartupBeaker
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
1,123subscribers
-58 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002503097460 |
|---|---|
| Type | Channel |
| Username | @StartupBeaker |
| Created | Between 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 16 September 2026 |
| Measurements held | 14 |
| Confirmed unchanged | 1 time, most recently 16 September 2026 |
| On Telegram | t.me/StartupBeaker |
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 18 September 2026 and assigned it the closest of 31 fixed categories, at 99% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Sept 2026, 10:38 | 1,123 | -2 |
| 12 Sept 2026, 16:01 | 1,125 | -10 |
| 8 Sept 2026, 12:21 | 1,135 | -10 |
| 2 Sept 2026, 23:07 | 1,145 | -5 |
| 30 Aug 2026, 11:38 | 1,150 | -4 |
| 27 Aug 2026, 07:14 | 1,154 | -3 |
| 24 Aug 2026, 10:54 | 1,157 | -5 |
| 20 Aug 2026, 20:16 | 1,162 | -5 |
| 17 Aug 2026, 13:24 | 1,167 | -3 |
| 14 Aug 2026, 09:24 | 1,170 | -4 |
| 11 Aug 2026, 07:02 | 1,174 | -5 |
| 8 Aug 2026, 11:59 | 1,179 | -2 |
| 7 Aug 2026, 23:46 | 1,181 | no change |
| 7 Aug 2026, 23:39 | 1,181 | first reading |
20 posts held, back to 6 June 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 5 August 2026. An engagement rate over an empty window would be a number about nothing.
6 reactions across 5 posts, in 4 distinct kinds. The most used accounts for 50.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 3 | 50.0% | |
| ⚡ | 1 | 16.7% | |
| 👍 | 1 | 16.7% | |
| 💔 | 1 | 16.7% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 7 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 6 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 6 June 2026 to 5 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Deal Velocity by MOST - texnologik startaplar uchun xalqaro akseleratsiya dasturiga qabul boshlandi MOST C-Space Hub Startup Booster bilan hamkorlikda o‘z mahsulotini kengaytirish va O‘zbekiston bozorida rivojlantirishga tayyor asoschilar uchun 8 haftalik dasturni ishga tushirmoqda. Dastur doirasida: • amaliy vorkshoplar va mentorlik sessiyalari; • startaplarni rivojlantirish uchun AI vositalari bilan ishlash; • xa…
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Ollama Hits $65M Series B: Open Models Go Mainstream Ollama closed $65M Series B (Theory Ventures lead). Total funding: $88M. What: Dead-simple way to run open-source AI models locally. No cloud vendor lock-in. No API costs. Traction: • 8.9M monthly developers • $65M Series B • Investors: Theory Ventures, Benchmark, 8VC, Y Combinator, Pace Capital Why it matters: Open models + local inference = lower costs, faste…
Etched: Harvard Dropouts Hit $10.3B in 7 Months Three founders dropped out, slept on floors, ran chip servers in a garage. Now: $300M Series C at $10.3B valuation. What: AI inference chips that run any model faster than GPUs. Already booked $1B in customer orders. How it happened: - 2022: Dropped out, zero fundraising experience - 2024: Shipped silicon, showed demos to Karpathy and Hinton - 2025: $1B in contracts …
Andera Raises $37M: AI Eats Enterprise Audit AI agents just automated internal audit—one of the most rule-bound, judgment-heavy enterprise workflows. Andera (founded 2024, Aryo Patel & Tinah Hong) raised $37M Series A led by Lightspeed + Bain Capital Ventures. The wedge: • Started with Fortune 100 customers • Proved 70% cost savings on control testing • AI agents read evidence, run tests, write workpapers in hours…
Cheap Chinese AI Models Are Killing Your Startup Advantage Almost 200 Silicon Valley founders just sent a letter to Trump urging him NOT to ban Chinese open-weight AI models like Kimi K3. Here's why this matters. The math: • Kimi K3: ~$0.50 per 1M tokens • Claude 3.5: ~$3 per 1M tokens • For a bootstrapped startup doing 10B tokens/month: $5k vs $30k If the US bans access, hundreds of early-stage startups die insta…
Physical AI robots are working factory shifts today—not tomorrow. Walden Robotics spun out of Toyota Research Institute in January 2026. By February, their wheeled humanoids were doing real work in a Toyota plant: loading parts, cleaning machinery, kitting components. Eight-hour shifts alongside humans. The move: Large Behavior Models let robots learn new tasks through real-world practice instead of manual reprogra…
OPEN MODELS ARE EATING CLOSED MODELS' LUNCH Ollama raised $65M Series B. Open-source AI is now the default for cost-conscious builders. What: Developers run LLMs locally on PCs. No API calls, no token limits. Founded by ex-Docker engineers. Proof: • 8.9M monthly developers • 176K GitHub stars • 85% Fortune 500 using it • 14 employees, 3 years to scale How: Free desktop tool → GitHub distribution → proved agentic …
Together AI: $800M Series C at $8.3B - Open-Source AI Infrastructure Wins Together AI just closed $800M Series C (post-$8.3B valuation) to power enterprise AI on open-source models. This is the biggest infrastructure play of Q2 2026. What it is: Cloud platform for training and running open-source AI models (DeepSeek, MiniMax, Kimi) at 10x lower cost than proprietary APIs. How they got there: - Founded 2022 to sol…
Enterprise AI Independence: Prime Intellect's $130M Bet Prime Intellect raised $130M Series A at $1B valuation to help enterprises build their own AI agents without relying on OpenAI or Anthropic Key metrics: - $100M ARR run rate (founded 2024) - Customers: Ramp, Zapier, Flapping Airplanes - Ramp's agent beat frontier models on accuracy while cutting costs 10x Why it matters: Every founder building AI products fac…
Bending Spoons: From Failure to $18B IPO Italian startup just went public at $18B—40% pop on day one. The real lesson: they turned a failed startup into a playbook for operational excellence. The Model: • Buy struggling SaaS brands (Evernote, Vimeo, Meetup) • Cut bloat, ship AI features fast • Revenue per employee: $1.12M (2023) → $2.57M (2025) How They Did It: • Failed first startup taught them luck is huge in ze…
Dispatch is the nerve center. Probook just raised $40M (A16Z + Sequoia) to unify home-services dispatch. Instead of bolting AI onto existing tools, founder George Eliadis built the entire OS around dispatch—lead intake, scheduling, billing, customer thread all in one. Why it worked: • Founder had domain pain (ran his father's pressure-washing biz) • Replaced 10+ point solutions with 1 integrated system • Customers …
8090 Labs Raises $135M Series A: Chamath's AI Coding Bet Chamath Palihapitiya just raised $135M for 8090 Labs, his AI coding agent for enterprises. He's stepping in as CEO full-time. The metrics: • $135M Series A (Salesforce Ventures led) • Product: Software Factory—AI agents that write production-quality code, not prototypes • Enterprise controls: audit trails, compliance, governance built-in • Investors: Katzenbe…
Showing the 12 most recent of 20 posts we hold for @StartupBeaker. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Named by 2 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 16 September 2026 — this entry's latest reading, not the date you are reading this.
“Startup Beaker” (@StartupBeaker), 1,123 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/StartupBeaker.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.