project rollup
Default
19767
mentions
across 19 keywords
across 19 keywords
net sentiment
+23%
6093 positive
12192 neutral
1482 negative
volume & sentiment over time
May 13 – Oct 18, 2026 · 4-day buckets
1–8 of 8 keywords
| keyword | mentions | net | trend | top theme | srcs | last seen | |
|---|---|---|---|---|---|---|---|
| timeline | 19466 | +61% | — | 1 | 14m | ||
| Opus 5.5 model documentation | 51 | +61% | claude / pricing | 2 | 2w | ||
| Opus 5.5 official announcement | 50 | +68% | pricing / model | 1 | 2w | ||
| SynthID | 16 | +100% | gemini / google | 1 | 2w | ||
| Cline | 149 | +72% | code | 3 | 3w | ||
| Quill | 32 | -10% | performance | 4 | 3w | ||
| Google SynthID AI image watermark discussion | 1 | +100% | — | 1 | 2mo | ||
| Opus 5.5 versus Claude Opus models | 2 | +100% | — | 1 | 3mo |
mentions
Showing 19676–19700 of 19767 mentions
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@bridgemindai Still just a leak, not an Anthropic announcement. Official lineup is still Fable 5.1 and Opus 5. If 5.5 actually ships at Fable-level quality and half the price, that would be the useful model. Watching. @bridgemindai Still just a leak, not an Anthropic announcement. Official lineup is still Fable 5.1 and Opus 5. If 5.5 actually ships at Fable-level quality and half the price, that would be the useful model. Watching.view source ↗
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Alibaba's Pingtouge just stood on stage and pounded its chest! Saying the quiet part out loud: it wants the model, the chip, the datacenter and the agent stack. All of it. Welcome back to Tuesday! And Qwen 4 is official! er, well, in training. Alibaba also laid out the roadmap: Qwen 4.5 and Qwen 5 are projected to s… Alibaba's Pingtouge just stood on stage and pounded its chest! Saying the quiet part out loud: it wants the model, the chip, the datacenter and the agent stack. All of it. Welcome back to Tuesday! And Qwen 4 is official! er, well, in training. Alibaba also laid out the roadmap: Qwen 4.5 and Qwen 5 are projected to scale into the 5–10 trillion parameter range, versus 2.4T for today’s Qwen3.8-Max. Careful reading X rumors, because some early headlines are already turning “future Qwen models up to 10T” into “Qwen 4 is a 10T model.” Alibaba did not say that. And being of sound mind, I thought, how the heck do you run that in China without Nvidia? Well, there's more. Its T-Head chip group unveiled Zhenwu V900, a training-and-inference accelerator that Alibaba says delivers 3× the performance of May’s M890, carries 216GB of memory, provides 1.2TB/s chip-to-chip bandwidth, and natively supports FP8 and FP4. The new Panjiu systems built around it are supposed to enter commercial production in Q1 2027, with Alibaba saying the architecture can ultimately scale a single cluster to as many as 500,000 cards which is obviously more than a few. Wow! Are you sure? The number looks ridiculous enough to make the 10T-model talk look considerably less theoretical. Yet, there it is. But Alibaba has history. Its current M890 supernodes run Qwen3.8-Max and Kimi K3, both above two trillion parameters, while the company says the Zhenwu family is already serving more than 650 enterprise customers. At the infrastructure level, Alibaba targets global cloud datacenter capacity above 20GW by 2032. Not exactly a startup putting “10T parameters” into a roadmap deck and hoping somebody finds GPUs later. Alibaba is trying to vertically integrate the entire thing. I'm curious how the two new Brazilian data centers announced in August will fit into these build outs, and chip plans. And file under just one more thing.... Buried underneath the giant-model headline Alibaba says Qwen3.8-Max hasview source ↗
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Wish Quill were open source. Great app but I don't trust a closed notes app with my second brain. Wish Quill were open source. Great app but I don't trust a closed notes app with my second brain.view source ↗
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The Quill sync bug bit me again. Lost edits after switching devices. Be careful. The Quill sync bug bit me again. Lost edits after switching devices. Be careful.view source ↗
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Quill's docs are seriously lacking. Spent an hour figuring out how templates work. Quill's docs are seriously lacking. Spent an hour figuring out how templates work.view source ↗
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Honestly Quill is just okay. Does the job but nothing groundbreaking. The docs are thin. Honestly Quill is just okay. Does the job but nothing groundbreaking. The docs are thin.view source ↗
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We rolled Quill out to the whole team. Setup was painful and the docs are missing half the features. We rolled Quill out to the whole team. Setup was painful and the docs are missing half the features.view source ↗
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AX – Google’s Open Agentic OrchestratorI have been happy with Google's Antigravity harness and Jules so looking forward to playing with this. Thanks for sharing. Simultaneously I am looking to also revisit local offline models. While I feel like I have a decent understanding of the model landscape I'm feeling a bit lost at which agentic harness to leverage … I have been happy with Google's Antigravity harness and Jules so looking forward to playing with this. Thanks for sharing. Simultaneously I am looking to also revisit local offline models. While I feel like I have a decent understanding of the model landscape I'm feeling a bit lost at which agentic harness to leverage for local models. Hermes, Cline, Aider, Qwen Code, Goose, Pi, OpenCode, something else? I live in the terminal so Desktop UX is a bonus but not a must have. Can I modify the antigravity settings/program to point to a local model? Where should I spend my energy?view source ↗
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Quill is closed source and that's a dealbreaker for me. Looking for an open alternative. Quill is closed source and that's a dealbreaker for me. Looking for an open alternative.view source ↗
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The pricing model killed it for me. $12/mo for notes I could keep in plain markdown? No thanks. The pricing model killed it for me. $12/mo for notes I could keep in plain markdown? No thanks.view source ↗
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Love that Quill is local-first and doesn't phone home. No telemetry, no account required to start. Love that Quill is local-first and doesn't phone home. No telemetry, no account required to start.view source ↗
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Quill crashed three times today on a large vault. Performance falls apart past 10k notes. Quill crashed three times today on a large vault. Performance falls apart past 10k notes.view source ↗
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Quill pricing is too high$12/mo is ridiculous when Obsidian is free. The app is nice but not that nice. $12/mo is ridiculous when Obsidian is free. The app is nice but not that nice.view source ↗
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Quill's keyboard shortcuts are fantastic. Feels like it was built by people who actually take notes. Quill's keyboard shortcuts are fantastic. Feels like it was built by people who actually take notes.view source ↗
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Quill is the best note app I've tried this year. Fast, clean, local-first. Highly recommend. Quill is the best note app I've tried this year. Fast, clean, local-first. Highly recommend.view source ↗
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https://t.co/Z64TY3xtha https://t.co/Z64TY3xthaview source ↗
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Quill is the first notes app where search is actually fast. Sub-100ms across my whole vault. Quill is the first notes app where search is actually fast. Sub-100ms across my whole vault.view source ↗
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Quill has become my daily driver for writing. The distraction-free mode is beautiful and fast. Quill has become my daily driver for writing. The distraction-free mode is beautiful and fast.view source ↗
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The sync feature is unreliable — lost a note yesterday after a conflict. Scary for a notes app. The sync feature is unreliable — lost a note yesterday after a conflict. Scary for a notes app.view source ↗
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Quill vs Obsidian?Switched from Obsidian to Quill last week. The UI is so much cleaner and it's way less bloated. Switched from Obsidian to Quill last week. The UI is so much cleaner and it's way less bloated.view source ↗
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I love that Quill stores everything as plain files. No lock-in, works with my git workflow. I love that Quill stores everything as plain files. No lock-in, works with my git workflow.view source ↗
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Ask HN: What's the most economical approach to the most tokens?I'm doing web developement, and game development for a hobby project. I've tried lots of harnesses / IDE's - Best I've found is VSCodium.+ Cline + Openrouter, using discounted models (GLM 5.3 Flash is 50% off atm for example) I used Cursor for the last year - it's been decent. But I'm unhappy with the direction their g… I'm doing web developement, and game development for a hobby project. I've tried lots of harnesses / IDE's - Best I've found is VSCodium.+ Cline + Openrouter, using discounted models (GLM 5.3 Flash is 50% off atm for example) I used Cursor for the last year - it's been decent. But I'm unhappy with the direction their going (it's largely just Grok Code at this stage...) Nobody advertises token limits - so it's pretty hard to compare, if you've used multiple tools in the last couple of months - what's your experience been? Will I be able to beat my Openrouter setup on cost per token via a useful model by subscribing to one of these? In my opinion - Grok 4.6 seems comperable with GLM 5.3 Flash. Deepseek 4.1 is my daily driver. I use Sol or Fable for hard problems - but it's expensive man... Please share your opinions.view source ↗
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Quill's markdown export is broken for nested lists. Reported it twice, no response. Quill's markdown export is broken for nested lists. Reported it twice, no response.view source ↗
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https://t.co/yo1DHXo2nx https://t.co/yo1DHXo2nxview source ↗
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Show HN: Slowave – local adaptive memory for coding agentsI started building Slowave because I kept running into the same problem with coding agents: every new session has the codebase and some documentation but not the context behind it, decisions that brought you there and especially the thinking process behind the code. Most memory system solutions focus primarily on the s… I started building Slowave because I kept running into the same problem with coding agents: every new session has the codebase and some documentation but not the context behind it, decisions that brought you there and especially the thinking process behind the code. Most memory system solutions focus primarily on the storage and retrieval aspects (vector search/RAG/graphs/ Markdown files, etc.). After months of storing memories (coding 8+ hours a day produces a lot of memories) these might hallucinate your reasoning model and they can clutter your context window. To treat semantic relationship, such as contradiction, supersession, etc, most systems added an extra LLM layer that summarize memories and continuously evaluate their semantic relevance. That comes with a non-negligible cost and introduces a split-brain system, where a second model is making decisions about memory independently of the agent actually using it. I started looking up into how human brain works, and the first thing striking me was that retrieval is just a part of the whole memory problem. Brain memories are a constant flow of information where what matters gets reinforced, what doesn't decays over time. What really matters for an efficient memory system is to retrieve memories that actually help (a human or an agent) to achieve its current task or goal given the current context. Everything else should be treated as noise. Slowave is my attempt to approach this problem differently: It instructs your coding agent to participate in maintaining its own memory. Each task becomes a feedback loop between your agent and the memory layer: remember -> recall -> use -> feedback -> reinforce / weaken -> decay Your agent tells Slowave whether retrieved memories were useful, irrelevant or stale. Slowave uses that signal to adapt those memories salience. Retrieval works upon this continuous loop of feedback, reinforcement or decay. This means Slowave doesn't need a separate LLM or LLM judge for memory maintenview source ↗