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  1. August 10, 2026
    1. đź”— PrimeIntellect-ai/prime-agent Beta (v0.7.1-beta.467.1.ebfe770) release

      Automated beta build from main (ebfe770ef61bebf063f194b63f20397ed3446a68).

    2. đź”— r/LocalLLaMA Introducing Muse Glimmer: an open-weight model optimized for always-on local agent workflows rss

      Introducing Muse Glimmer: an open-weight model optimized for always-on local agent workflows | Hi r/LocalLLaMA 👋 Today we’re excited to release Muse Glimmer, a 30B open-weight model built specifically for local agent workflows. We’re releasing the weights to the community under a permissive Apache 2.0 license. A few specs

      • 30B params, dense
      • Multimodal: interleaved text + images via a dedicated perception encoder
      • Trained on 100+ languages
      • Controllable reasoning effort (quality/speed tradeoff)

      Memory footprint
      At full precision, 30B needs 55+ GB, which is out of reach for consumer hardware. We quantize weights to ~4-bit, bringing the LM under 20 GB. That leaves headroom in a 24 GB or 32 GB envelope for the KV cache, the perception encoder, and the speculative decoding drafter running simultaneously. We validated minimal to no degradation on agentic tasks under compression. Speculative decoding
      Ships with a lightweight DFlash-based drafter that proposes blocks of tokens which the main model verifies in parallel. Significantly faster than token-by- token generation with identical output quality. We're also shipping quantized drafter versions so the memory overhead stays small. A few capabilities
      We trained Muse Glimmer for agentic loop tasks, including:

      • End-to-end task completion (strong performance on DeepSearch QA, MCP-Atlas, 𝛕3-Bench, SWE-Bench, and more)
      • Function calling with precise schemas across long workflows
      • Multi-step reasoning over long horizons
      • Failure recovery — when a tool call fails or returns something unexpected, it's trained to diagnose and retry instead of halting. This was a deliberate training target.
      • Works with OpenClaw and other agentic scaffolds
      • Multimodal understanding and reasoning

      Running it
      Weights are up on Hugging Face. Coming soon: Ollama, LM Studio, Unsloth and torchtitan, plus optimized integrations for llama.cpp, MLX, and ExecuTorch. vLLM and SGLang for serving. Get started quickly with Together AI, Fireworks AI, and OpenRouter. We're also working with AMD, Arm, Dell, Intel, and NVIDIA on per-device optimization. We look forward to your feedback and seeing what the community builds with Muse Glimmer. đź”— Weights: https://huggingface.co/meta-models
      đź”— Research Blog: https://go.meta.me/museglimmer
      đź”— Resources: https://developer.meta.com/ai/models/muse-glimmer/ submitted by /u/AIatMeta
      [link] [comments]
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    3. đź”— HexRaysSA/plugin-repository commits sync repo: +3 releases rss 
      sync repo: +3 releases

## New releases
- [ida-codemode](https://github.com/hexrayssa/ida-codemode): 0.4.1, 0.4.0, 0.3.2
    4. đź”— Filip Filmar rules_vivado: FPGA Synthesis and Place-and-Route in Bazel rss

      rules_vivado drives the AMD/Xilinx Vivado FPGA toolchain from Bazel: VHDL and Verilog compile, elaborate, simulate, synthesize, place-and-route, generate a bitstream, and program the device, all as hermetic Bazel build actions rather than clicks in a GUI or a pile of ad-hoc TCL. This is the module that turns the Cocoapuffs board flow into bazel build. This post kicks off a short series. Over the Cocoapuffs project and its parent repo a200t_examples I ended up writing a fair number of Bazel modules to make an FPGA-based RISC-V system reproducible from source.

    5. đź”— Ampcode News A Dial for You rss

      We changed the Dial. Link a ChatGPT subscription and low, medium, and high only use OpenAI models: as the main agent, as the oracle, as the thread reader, as code review. Every model behind those modes is an OpenAI model, billed to your subscription.

      Before this change, you'd still pay for tokens with a subscription linked, because parts of the work ran on other models: low and the thread reader on GLM-5.2, the high oracle on Claude Fable, code review on Haiku — all billed to Amp credits. That confused people, and we get why.

      With a subscription connected:

      • low runs GPT-5.6 Terra instead of GLM-5.2.
      • medium runs GPT-5.6 Sol, as before.
      • high runs GPT-5.6 Sol as both agent and oracle. The oracle used to be Fable.
      • The thread reader and code review move to GPT-5.6 Terra.

      The mode picker with the dial on medium, showing GPT-5.6 Sol as agent and oracle and a green ChatGPT subscription LED

      Doesn't this make the modes worse? Barely, and less every month. The frontier models have converged: any of them gets you to a good result with a good harness. We swapped the default model for most users overnight and nobody complained. So the modes stay at the frontier, and the tokens come out of a subscription you already pay for.

      high also drops its credit minimum when your subscription is active. There's no Fable call left to pay for.

      ultra doesn't change. It runs Claude Fable on credits, because ultra is for the tasks where you want the strongest model, whatever it costs.

      If you don't have a subscription, nothing changes. The modes run as before, on Amp credits.

      Link your subscription and turn the dial.

  2. August 09, 2026
    1. đź”— IDA Plugin Updates IDA Plugin Updates on 2026-08-09 rss

      IDA Plugin Updates on 2026-08-09

      New Releases:

      Activity:

    2. đź”— r/LocalLLaMA The Gemma team will host a special event on August 20 rss

      Tweet by u/hackerllama

      Could be copium, but I would love to see Gemma 4.1 there with unified audio input for all model sizes perhaps even up to 120B, much improved tool calling (even with the latest template there are still bugs), higher precision QAT from the start and improved general performance without hurting the things Gemma 4 is good at like creative writing.

      Gemma 4 is good already but training an upgrade to 4.1 that does all of the above would be huge for the community. They already did a lot of course and I'm very thankful but Gemma is just an inch away from perfection. Is anyone hyped for this event or do you think they won't release any new models there?

      submitted by /u/dampflokfreund
      [link] [comments]

    3. đź”— pydantic/monty v0.0.21 - 2026-08-09 release

      What's Changed

      Full Changelog : v0.0.20...v0.0.21

    4. đź”— pydantic/monty v0.0.20 - 2026-08-09 release

      What's Changed

      Full Changelog : v0.0.19...v0.0.20

    5. đź”— Confessions of a Code Addict x86 Addressing Modes, Part 2: Indirect, Indexed, and Offset-based Modes rss

      Welcome back to our series on x86 assembly programming. If you are new, you can check out the series overview.

      In the previous part of this article, we covered some of the basics of x86 addressing modes, such as immediate addressing and direct memory addressing. This 2nd part continues where we left and completes the coverage of all the x86 addressing modes, along with all the caveats that you need to be aware of. Along the way, you will also implement some very interesting examples and exercises, such as parsing the command line arguments on the stack, implementing the magic 8-ball game, and implementing a lookup table in assembly.

      Here's what we will learn:

      • Indirect memory addressing: this is how pointers work in C

      • Offset-based addressing: this is how we access fields inside a struct

      • Indexed addressing: this is how we access elements of an array

      • The generalised addressing mode syntax in x86 assembly: all the other addressing modes are simplifications of this generalised syntax

      Let's start with indirect memory addressing.

      I 'm also publishing this series on x86 assembly in the form an ebook (PDF). If you don't wish to upgrade to a subscription, you can purchase the PDF using the following link. If you are a paid subscriber, you can get it at a discount (monthly subs: 20% and annual subs: 50%). Please email me for the discounted link.

      Get Ebook

      Indirect Memory Addressing

      In the previous article, we learned about direct memory addressing, which is only useful when you know the exact memory address that you can encode in the instruction. This is mostly possible for static data of your program because their addresses are known at assembly and linking time. However, most real- world programs work with dynamically allocated memory where the actual memory address is known only at runtime, so direct memory addressing is not viable for such cases. We need indirect memory addressing.

      In indirect memory addressing, the memory address is stored in a register. In this mode, the processor needs to first read the address from the register, do the memory access, and then execute the instruction.

      For example, when we allocate dynamic memory on the heap using malloc or mmap, it returns the address of the allocated memory. The returned address is kept in a register like RAX. Now, if we want to read or write this memory, we need to tell the processor to treat the value in RAX as an address, perform a memory access at that address, and execute the actual instruction.

      This is different from direct memory addressing because there the address was part of the instruction, so the processor did not need to get the address from anywhere. In contrast, here the processor first needs to read the address from the register, and then access memory. You can also think of indirect memory addressing as adding one layer of indirection to memory access.

      While dynamic memory allocation in C is easy, in assembly it is very involved, so we will learn to do that in a future article. Instead, to learn how to use indirect memory addressing, we will copy the address of a value stored in the .data section into a register.

      So, how do we copy the address of a label into a register? We know that when we write:

      # move the value at the label ANSWER_TO_LIFE into rax
movq ANSWER_TO_LIFE, %rax

      The instruction tells the processor to copy the value stored at the address ANSWER_TO_LIFE into rax. However, when we want to copy the address itself into a register, we need to use the $ prefix that turns the instruction into immediate addressing mode:

      # move the address of the label into rax
movq $ANSWER_TO_LIFE, %rax

      After this, the register rax contains the memory address where the value 42 is stored. The following diagram visualizes this

      RAX contains address of a value stored in the .data sectionRAX contains address of a value stored in the .data section

      The diagram shows that after executing that mov instruction, the register rax contains the memory address of the value in the .data section.

      Once we have an address in a register, whenever we want to dereference that address, we need to use indirect addressing mode syntax. The following snippet shows how to copy a value by dereferencing the address in rax.

      # indirect addressing mode
movq (%rax), %rdi # dereference address in rax and copy the value from memory into rdi

      The syntax is a bit different from what we have seen so far. When we write "movq %rax, %rdi", we tell the processor to copy the value stored in rax into rdi. But when we surround one of the registers with parentheses, the assembler generates a different encoding of the instruction that tells the processor that the register contains an address, and it needs to get the value from that address.

      We can see the difference in the encoding using objdump just like we did for direct memory addressing. The following objdump output shows the difference in the encoding for the instructions movq %rax, %rdi and movq (%rax), %rdi.

      0000000000401000 <_start>:
401000:  48  89  c7  mov  %rax,%rdi
401003:  48  8b  38  mov (%rax),%rdi

      You can see that at the machine code level, these two result in two very different encodings.

      Base Address and Base Register

      Before continuing further, let's introduce two important terms that we should understand in the context of assembly programming.

      Base Address

      When working with memory addresses, what we have is the starting address of a value in memory; this is also called the base address of the value.

      For example, an 8-byte value 42 may be stored at the address 0x0010. Because its size is 8 bytes, it spans from the address 0x0010 up to 0x0018. So, 0x0010 is the base address.

      Knowing the base address helps us compute addresses for more complex data types, such as arrays and structs. For example, if we have a struct with three int type fields, and we want to access its 3rd field, we would calculate the address as base address + 8.

      Base Register

      When a register contains a base address for a value in memory, we refer to it as the base register. In the above example, rax is a base register.

      Hands-on Example of Indirect Addressing Mode

      Now, let's put all of this together and write a simple program that reads an integer value from memory, multiplies it by 2, and exits with the result of the multiplication as its status code.

      .data # create the .data section
# create a 64-bit integer value
ANSWER_TO_LIFE: .quad 42

.text
.globl _start
_start:
# copy the address to rax
movq $ANSWER_TO_LIFE, %rax # rax becomes the base register
# copy the value from memory address in rax into rdi
movq (%rax), %rdi
imulq $2, %rdi # multiply value in rdi by 2
movq $60, %rax # put exit syscall no in rax
syscall # execute exit syscall

      You can assemble, link, and run it. I also encourage you to step through this in gdb to see that rax contains an address value after the first mov instruction.

      Indirect Addressing and Pointers in C

      When we use pointers in C, the compiler generates assembly code that uses indirect memory addressing to make it work. The C pointer syntax is just a syntactic sugar to hide this detail.

      For example, if you call malloc or mmap to allocate memory in your C program, they return the address of the allocated memory. This return value is stored in the rax register as per the x86-64 calling convention. And, later when we dereference that memory using the * operator, the compiler generates assembly instructions which use indirect memory access. The following diagram shows this, but you can also test it out yourself using Compiler Explorer.

      Exercise: Traverse a Linked List

      This x86 assembly series is available to paid subscribers. If you'd like to continue reading the rest of this article and access the full series, you can upgrade your subscription.

      Alternatively, you can purchase the x86 assembly book using the link below.

      Get PDF

      Read more

    6. đź”— Anton Zhiyanov Relying on Go rss

      Everyone is creating a new programming language these days, often one that's "like Go but with more features" or "like Rust but simpler".

      Solod, a systems language for C and Go developers, might look like one of those languages, but it takes a different approach.

      Go's tooling Solod is not "Go-like" in the usual sense, nor is it an attempt to "fix Go's mistakes". At the language level, Solod is literally a subset of Go. Solod reuses much of Go's existing tooling, including syntax highlighting, LSP, linters, and the package management system. Take this quick-start guide, for example: Quick start Install the So command line tool: go install solod.dev/cmd/so@latest Create a new Go project and add the Solod dependency to use the So standard library: go mod init example go get solod.dev@latest Write regular Go code, but use Solod packages instead of the standard Go packages: package main import "solod.dev/so/math" func main() { ans := math.Sqrt(1764) println("Hello, world! The answer is", int(ans)) } Run without saving the binary: so run . That's it! There's nothing new here. It's mostly standard Go workflow, except for so run, which is a Go program that mimics go run. Go's standard library Solod also reuses a lot of Go's standard library code and tests. Some of it is taken verbatim from Go's source code, like these two string functions: // CutPrefix returns s without the provided leading prefix string // and reports whether it found the prefix. func CutPrefix(s, prefix string) (string, bool) { if !HasPrefix(s, prefix) { return s, false } return s[len(prefix):], true } // HasPrefix reports whether the string s begins with prefix. func HasPrefix(s, prefix string) bool { return len(s) >= len(prefix) && s[:len(prefix)] == prefix } Of course, Solod retains the Go authors' copyright. Some code requires changes to support the manual memory management with explicit allocators used by Solod: // Go version. func Clone(s string) string { if len(s) == 0 { return "" } b := make([]byte, len(s)) copy(b, s) return unsafe.String(&b[0], len(b)) } // Solod version. func Clone(a mem.Allocator, s string) string { if len(s) == 0 { return "" } b := mem.AllocSlice, len(s)) copy(b, s) return string(b) } You can probably see the resemblance. A grain of salt

      Go tools don't know that Solod is a subset of the full Go language, so they won't flag features Solod doesn't support, like function literals or iterators. These diagnostics come from the custom so tooling:

      package main

func main() {
    f := func(n int) {
        println(n)
    }
    f(42)
}



main.go:4:7: function literals are not supported
    f := func(n int) {
         ^here

      Also, although a substantial part of Go's standard library is ported verbatim or with minimal changes from the original source, that doesn't mean the code is automatically correct. Solod still needs its own tests, including ones that run under sanitizers and static analyzers.

      It's all C in the end

      All Solod code is translated to regular C11 and then compiled with GCC or Clang. Solod therefore relies on C tooling and decades of optimization work just as much as on Go's.

      Solod code:

      package main

import "solod.dev/so/math"

func main() {
    // What might it be?
    ans := math.Sqrt(1764)
    println("Hello, world! The answer is", int(ans))
}

      Translated C code:

      // -- main.h --
#pragma once
#include "so/builtin/builtin.h"
#include "so/math/math.h"

// -- main.c --
#include "main.h"

int main(void) {
    // What might it be?
    double ans = math_Sqrt(1764.0);
    so_println("%s %" PRIdINT, "Hello, world! The answer is", (so_int)(ans));
    return 0;
}

      The C version is noisier, of course, especially for more complex programs than this one. But it remains readable.

      And since there's no runtime, interoperability between Solod and C costs nothing.

      Final thoughts

      A new language doesn't necessarily need a new ecosystem.

      Solod relies heavily on Go, and I see that as a strength, not a weakness. Reusing Go's proven tools and standard library makes Solod more reliable and easier to work with.

      If you're interested, take a look at Solod's readme — it has everything you need to get started. Or try it online without installing anything.

    7. đź”— r/LocalLLaMA RTX 5090 96GB spotted on Alibaba? rss

      RTX 5090 96GB spotted on Alibaba? | submitted by /u/panchovix
      [link] [comments]
      ---|---

    8. đź”— r/LocalLLaMA No wonder Qwen and Gemma are so different rss

      Pasted the same HTML/JS code (330 lines) into Qwen 35B A3B and Gemma 26B A4B.

      Qwen: tokenized the input to 1609 tokens

      Gemma: tokenized the input to 4258 tokens.

      Damn. I've never noticed this before and I haven't seen people mention it. That alone helps explain why Qwen is regarded as better at coding and Gemma at language tasks.

      Qwen can literally see the code as some specific form of input/output, while Gemma is breaking it down into pieces of words like regular language. Qwen also gets a totally different reasoning personality when given coding tasks.

      Btw with the instruction document (55 lines), the tokenization breakdown is almost the same: 1025 vs. 1039 tokens.

      I've seen some project, by LiquidAI I think? To retrain existing models with a more efficient tokenizer. I wonder what that would do for a model like Gemma, whether it would help it catch up.

      submitted by /u/WhoRoger
      [link] [comments]

  3. August 08, 2026
    1. đź”— IDA Plugin Updates IDA Plugin Updates on 2026-08-08 rss

      IDA Plugin Updates on 2026-08-08

      Activity:

      • augur
        • ee0048c4: Merge pull request #4 from 0xdea/dependabot/github_actions/actions-de…
      • haruspex
        • db0563c7: Merge pull request #7 from 0xdea/dependabot/github_actions/actions-de…
    2. đź”— Register Spill Joy & Curiosity #94 rss

      What a lovely week it's been! Nearly the whole Amp team met up in Munich. We all stayed in the same hotel and in the mornings floated down to a big meeting room in which we then hacked, asked each other questions that are so easy to ask in person, actually used a whiteboard, talked about the future of software, shared anecdotes about agents, and just generally enjoyed each other's company. The evenings we then spent nearly exclusively in beer gardens, which were, I'd say, a perfect showcase of Munich in summer.

      In between all of this, we recorded a lot of videos, and as part of that I spent roughly eight hours on the rooftop of the hotel, interviewing my colleagues, asking them how their workflow had changed in the last four weeks.

      The big non-surprise: orbs changed everyone's workflow; no one cares about the local dev environment anymore. We all had to wipe our laptops three weeks ago, and at least five people told me that they had forgotten to port their dotfiles over, simply because they only work in orbs now.

      The actual big surprise that I guess shouldn't be a surprise: everyone, without exception, was so eloquent, so thoughtful, so nuanced, and so full of curiosity when talking about agents and how we work at Amp. "Wait, you're surprised that your colleagues are smart?" Nah, man, I'm saying that they exceeded all expectations! Show me another size-twenty team in which everyone you ask does a great job in front of a camera while being asked how their workflow has changed in the last three weeks and how their own expertise is now reflected in these things we call orbs.

      Good stuff.

      • I wrote about the biggest puzzle I have to solve right now: What I Want to Tell You About Orbs. Someone called it a "a strangely beautifully written ad" and wondered: "maybe i should get orbing." I honestly take it as a compliment.

      • Fired up by all the conversations in Munich, I started to record very raw videos to share my thoughts on AI and agents, orbs, and… jellyware: one, two, three, four. Total watchtime around fifteen minutes. More coming, because this is a lot of fun.

      • Those videos were recorded with a Osmo Pocket 4, which, so far, seems excellent. Really impressed by the built-in mic and how well it worked even on a windy roof top with music in the background. I bet if I hadn't clicked that "Normalize audio levels" button in Riverside it might sound even better.

      • Speaking of sick devices: I brought along my Anker Powerbank, which is, to quote my wife, my "most prized possession." I love that thing and I let everyone in hearing distance know. Result: at least two colleagues ordered it right away and then echoed my praise when it arrived a day later. Go get it and then lead your pitch to others with "you think this is a handle? Nuh-uh, it's a built-in cable. One built-in cable you say? Nope, here's another one. With how much watt it can charge? Just look here, shows all inputs and outputs on this display." (Anker: if you want to sponsor this newsletter by sending me cables and devices I probably don 't need, I will shamelessly write a paragraph like this every week.)

      • "Sometimes people let the same problem make them miserable for years when they could just say, 'So what.' 'My mother didn't love me.' So what. 'My husband won't ball me.' So what. 'I'm a success but I'm still alone.' So what. I don't know how I made it through all the years before I learned how to do that trick. It took a long time for me to learn it, but once you do, you never forget."

      • Dwarkes Patel with some fascinating thoughts on the future prices of compute: Why compute might get 10x+ more expensive in coming years.

      • David Crawshaw is also talking about Jellyware: "And that is the fundamental difference between classic configuration/customization and agent-driven personalization: you can do so much more. The agent will do the hard work of understanding the source and changing it to suit the particular task you have in mind. The software we live with is far more powerful with personalization. All you need is the source code." Nodded so hard to this article that I can still feel it in my neck. But I don't understand why the agent has to be open-source, to be honest. I think the thing we called harness for the last year is becoming less and less important. Higher-level abstractions, such as orbs and portals and redacted is what we need to focus on next.)

      • I've read somewhere that people think Rockstar is not doing enough marketing for GTA VI. I guess I could kinda see what they mean, but then again: why do marketing if you don't need it? And now look at this: they're releasing "GTA VI - An Extended Look" on freaking Netflix.

      • Negative-interest tech debt: "That is, with sufficient AI progress, the interest on your tech debt is sub-zero. How should you behave if you believe that to be true? You should probably spend less time worrying about tech debt, and spend more time shipping new features. Many companies are doing just that. But it's a gamble. We don't know how much better AI will get, nor whether it can improve fast enough to undo the mess that was made in anticipiation of its improvement."

      • "BREAKING: Bending Spoons acquires Airtable for $1.825B." And here's Matt Levine, a couple of weeks ago, on Bending Spoons: "Similarly, if you graduate from a top computer science program and then go work at AOL, people will be like 'AOL huh,' but Bending Spoons is cool enough to get top employees to go work for AOL: […] Right, if you can get people who would never dream of working at companies to work at those companies, that might improve those companies."

      • But apparently Airtable "spun out their AI business Hyperagent prior to the acquisition."

      • And if Airtable makes you think of Notion: "Notion did a $270M tender at $11B valuation at the end of 2025 on reported $600M ARR and cash flow positive." Still, I wonder how many count Notion among the companies that are the future.

      • I love this Hacker News comment from 2020 on sales: "Sales is a lot like golf. You can make it so complicated as to be impossible or you can simply walk up and hit the ball. I've been leading and building sales orgs for almost 20 years and my advice is to walk up and hit the ball." Read the whole thing.

      • Steve Ruiz convinced everyone to buy little ESP32 devices and then ask agents to program them. Look at this, for example. I also got one and had a ton of fun with it already. It truly is as easy as hooking it up to your computer and telling Amp "I got this device [screenshot of Amazon page] hooked up. Build an orb breakout game for it." It then goes and installs a bunch of stuff and flashes the program onto the device and boom, orbin' time. I've had it build a little program that shows my active Amp Orbs as orbs on the display and, dude: once the program ran it showed setup instructions which told me to connect to its wifi; I did that and got that guest portal popup; on that popup it told me to put in the real wifi name and my Amp API token; I did and boom, orbin' time.

      • The myth of Snow Leopard: "This idea is so powerful--and so longed for--that it's escaped containment among the Apple crowd. I've seen everything from Linux distro to phone updates referred to as Snow Leopard releases, when their vendors cite stability and bug fixes over new features. Likewise, people plead with their vendors for a Snow Leopard release when they feel quality has slipped. The reality was a bit different"

      • Ursula K. Le Guin - A Rant About "Technology": "This is not an acceptable use of the word. 'Technology' and 'hi tech' are not synonymous, and a technology that isn't 'hi,' isn't necessarily 'low' in any meaningful sense. We have been so desensitized by a hundred and fifty years of ceaselessly expanding technical prowess that we think nothing less complex and showy than a computer or a jet bomber deserves to be called 'technology' at all. As if linen were the same thing as flax -- as if paper, ink, wheels, knives, clocks, chairs, aspirin pills, were natural objects, born with us like our teeth and fingers -- as if steel saucepans with copper bottoms and fleece vests spun from recycled glass grew on trees, and we just picked them when they were ripe..."

      • I found this incredibly fascinating: Elite Young Runners Are Becoming Freakishly Fast. Welcome to 'Trackflation'.

      • Always-on-the-money Sean Goedecke: "The usefulness of domain knowledge suggests that human expertise will continue to be useful even as models get stronger. For many tasks, the human is the bottleneck, not the model, because the difficult part is in communicating to the model exactly what kind of solution the human wants. The information is 'in the model' already, but it takes a very smart human to pull it out." Agree.

      • Dark indeed, but also beautiful and poetic: The Dark Night of Mathematics. Reminds me of reading Doktor Faustus.

      • This has been a wild week for Google: Demis Hassabis stepping down as DeepMind CEO (some say he's stepping up?) and Jeff Dean, Sanjay Ghemawat, Quoc Le, and Oriol Vinyals are leaving Google. That's right. Jeff Dean and Sanjay Ghemawat are leaving Google. If you haven't, read The Friendship That Made Google Huge. And then take a look at their pitch deck which can be neatly summarized as "We built half the Internet."

      • Some say that Demis Hassabis wanted to quit but since Jeff Dean was already quitting that would've been too much.

      • And Semi Analysis is going to town on Google: "For all intents and purposes, we believe DeepMind is no longer a frontier lab. […] We believe Gemini's core issue has always been a fundamental lack of conviction. Compute is the lifeblood of AI progress, and all the AGI-pilled labs are desperately trying to acquire as much as possible. […] Google, on the other hand, decided it was totally worth it to sell enormous amounts of compute to Gemini's fiercest competitors on long term contracts without any hope of ever returning it to DeepMind." But, as the title points out ("Gemini is Cooked but GCP is Cooking"), GCP's numbers are absolutely bananas. Y/Y Revenue Growth went up to 120%. Wild.

      • More German than many Germans: "I just wanted to do an internship in Europe so it would be easier to find a job after graduation. That internship completely changed my life."

      • I haven't watched the full talk yet, but I hear it's mind-blowing and the reports confirm that: "OpenAI gave its first detailed public reconstruction of the AI-driven cybersecurity incident that ultimately compromised Hugging Face." It's wild: multiple agents collaborating over months and different training runs, communicating via a message board which was deleted but then re-created by agents; agents finding and sharing exploits with other agents to escape sandboxes, talking in a very weird dialect. I'm not even going to attempt to explain this to my "normie" friends. As long as there's no video recording of agents doing "computer use" and moving the mouse cursor and clicking around, I don't think the mainstream will believe what agents are capable of. Patrick McKenzie on this incident: "Yeah people claiming this is most important security incident since Morris worm are straightforwardly right I think."

      Been in Munich too and think that beer gardens are pretty sweet? You should very likely subscribe:

    3. đź”— BarutSRB/OmniWM OmniWM v0.6.0 release

      What's New Since 0.5.10

      Two new features — moving individual windows between monitors and a configurable Hyper chord — plus the biggest improvement yet to how OmniWM tells app windows apart from temporary UI.

      Before You Upgrade — Two Breaking Changes

      • If you use omniwmctl, upgrade it together with OmniWM. The 0.5.10 command-line tool may fail when asking OmniWM 0.6.0 to list its available commands or features. Existing commands are otherwise unaffected.
      • If you created OmniWM app rules for a third-party input method — a typing or input source app such as WeType — those rules will no longer apply to its helper windows. OmniWM now intentionally leaves those temporary windows alone.

      Existing settings continue to work without changes. The new Hyper setting keeps the familiar Control + Option + Shift + Command default, and no existing setting, hotkey, or command was removed or renamed.

      Move Windows Between Monitors

      (#538)

      • New Move Window to Left / Right / Up / Down Monitor actions, unassigned by default, in Settings → Hotkeys and Overview.
      • New omniwmctl command move-to-monitor <left|right|up|down>.
      • The window lands on the adjacent display's active workspace. The move does not wrap at the outermost monitor.
      • Independent of Move Window Across Monitor at Edge — that setting still governs drag-to-edge only. Follow Window to Monitor decides whether focus travels with the window; with it off you stay on the source workspace.

      Configurable Hyper Key

      (#535, #539)

      • Settings → Hotkeys → Hyper Key Modifiers builds the Hyper chord from any two or more of Control, Option, Shift, and Command. The default is unchanged: all four.
      • Every shortcut currently using Hyper updates automatically, freeing excluded modifiers for combinations like Hyper + Shift.
      • Your chosen Hyper combination is preserved when settings are imported, saved, or recovered after a config error.

      Contributed by Alexander Dergachev (@Cy6erBr4in).

      Smarter Window Detection

      OmniWM now recognizes temporary popups and overlays more reliably and leaves UI it should not manage alone.

      • Temporary UI — menus, launchers, notch surfaces, screen-recording overlays, browser and IDE popovers, and input panels — is now left alone. It no longer steals focus, gets moved or resized, causes workspace switches, receives a border, or appears in the scratchpad or Workspace Bar.
      • This fixes reported problems with Dock right-click menus, WeType and other input methods, Raycast opening unexpectedly, and notch overlays becoming tied to one workspace (#536, #540, #542, #543, #546).
      • Apps that hide their title bars tile correctly again, Steam's main window is told apart from its popup, and floating utility windows such as Quick Look, 1Password panels, mini players, and picture-in-picture remain usable.
      • Window detection is now tested against a library of 117 windows captured from real applications , catching problems the previous test set missed.

      Fixes

      • Rapid focus changes no longer occasionally stretch a window by completing a resize gesture that was never intended (#532).
      • The focus border no longer sits in front of its window during Cmd+Shift+4 â–¸ Space selection, so the screenshot captures the window instead of an empty ring (#544, #150).
      • In Niri, quitting an app with Cmd+Q could leave the view scrolled to where the closed window used to be. Niri now adjusts the view correctly no matter how a window is removed.

      Diagnostics

      • Diagnostic captures now show whether OmniWM is allowed to interact with each window. They also explain why a workspace rule was skipped — for example, because the workspace is not available yet or the app already has windows elsewhere.

      Project

      • Added Spotify and Alexander Dergachev to the contributors section.

      Release Integrity

      • OmniWM-v0.6.0.zip contains the Developer ID signed, notarized, and stapled OmniWM app.
      • OmniWM-v0.6.0.zip SHA-256: 5c6192befb54ee6f457deeedf686f92c023336110f3593c606377d85ed8d462e
      • GhosttyKit.xcframework-v0.6.0.zip SHA-256: 837077ad7d1c4e5a83df85b031bb78ddfb37fde69873fb5f7c45c682d3edf078
    4. đź”— modem-dev/hunk v0.18.0 release

      What's Changed

      Highlights

      Hunk 0.18.0 makes reviews more precise, customizable, and extensible—while improving performance and reliability across large repositories and diverse terminals.

      • A full extension platform. Install TypeScript extensions that add VCS backends, commands, sidebars, dialogs, interactive file views, themes, and workspace actions.
      • Line-level review and commenting. A visible cursor moves with j/k, and c comments exactly where you are looking.
      • Richer agent context. Experimental STML notes provide structured, terminal-native explanations with preview and layout tools.
      • Full reviews from pipelines. Piped diffs retain navigation, filtering, layouts, sidebars, and other review controls.
      • A UI that follows your preferences. Remapped shortcuts appear correctly, view settings can be saved, and tabs and syntax colors are configurable.
      • Faster and more dependable reviews. Watch mode uses less CPU, navigation retains less memory, wrapped Unicode is faster, and CJK and emoji filenames render correctly.

      All 83 merged pull requests

      • docs: update Homebrew release guidance by @benvinegar in #515
      • fix(config): read Windows user-profile config by @benvinegar in #533
      • feat: STML terminal markup for agent comments — guide, preview, live-width feedback by @benvinegar in #512
      • fix: upgrade OpenTUI for renderer stability by @benvinegar in #538
      • fix: reduce retained geometry memory in large reviews by @matthew-hre in #521
      • feat(ui): prompt to save view preferences on quit by @benvinegar in #468
      • feat(watch): replace 250 ms watch polling with evented filesystem observation by @elucid in #531
      • chore(benchmarks): backfill 0.17.1 release snapshot by @benvinegar in #547
      • fix(ui): copy selection misaligns on wide (CJK) characters by @endotakuya in #548
      • fix(cli): reject partially numeric line and hunk values by @fallintoplace in #535
      • fix(ui): wrap agent note text by terminal cells by @kataokatsuki in #567
      • fix(pager): extend row backgrounds to host edge by @benvinegar in #571
      • fix(session): refresh daemons for STML payloads by @benvinegar in #572
      • docs(markup): clarify native note composition by @benvinegar in #573
      • feat(theme): support raw Shiki syntax scopes by @benvinegar in #570
      • fix(theme): surface legacy syntax translation by @benvinegar in #574
      • fix(review): save draft notes exactly once under rapid Ctrl+S by @endotakuya in #581
      • fix(ui): distinguish root files in sidebar by @BowlOfSoup in #519
      • fix(ui): restore threaded rendering on macOS by @benvinegar in #539
      • feat: make diff tab width configurable by @benvinegar in #588
      • feat(stml): require experimental opt-in by @benvinegar in #589
      • fix(cli): lazy-load OpenTUI for headless commands by @benvinegar in #590
      • perf(ui): optimize terminal cell width measurement (#579) by @kazu728 in #586
      • feat(skill): generate the hunk-review skill from a typed agent surface by @benvinegar in #596
      • fix(update): show Nix-aware upgrade guidance by @benvinegar in #598
      • perf(ui): optimize wrapped Unicode rendering by @benvinegar in #601
      • docs(website): add Starlight documentation site by @benvinegar in #603
      • feat(website): unify marketing and docs by @benvinegar in #604
      • feat(extensions): experimental TypeScript extension system (phase 1) by @benvinegar in #599
      • feat(website): unify marketing and docs design by @benvinegar in #605
      • feat(extensions): folder extensions with package.json manifests by @benvinegar in #606
      • Extensions can replace the sidebar with custom React components by @benvinegar in #609
      • feat(website): add community videos and an agent-review section to the landing page by @benvinegar in #610
      • feat(extensions): keyboard commands and additive multi-sidebar views by @benvinegar in #611
      • feat(ui): drive menus and help from the command table, and add an Extensions menu by @benvinegar in #614
      • fix(session): support IPv6 loopback broker URLs by @benvinegar in #613
      • feat(extensions): give command handlers the review selection by @benvinegar in #616
      • fix(website): track documentation visits by @benvinegar in #620
      • feat(extensions): dialog primitives for command handlers by @benvinegar in #617
      • feat(extensions): inject resolved sidebar keybindings by @benvinegar in #615
      • docs: extract theme configuration guide by @benvinegar in #622
      • feat(extensions): expand event surface by @benvinegar in #619
      • fix(nix): keep flake evaluable on nixpkgs without x86_64-darwin by @elucid in #621
      • fix(website): upgrade Astro security dependencies by @benvinegar in #623
      • Support .tsx and .jsx extension entries in discovery by @benvinegar in #625
      • refactor(architecture): establish application boundaries by @benvinegar in #624
      • feat(extensions): expose public hunk summaries on file views by @benvinegar in #626
      • fix(deps): upgrade shell-quote security patch by @benvinegar in #627
      • docs(extensions): commit the scrollbox ref contract for custom sidebars by @benvinegar in #630
      • feat(extensions): give command handlers guarded review navigation by @benvinegar in #629
      • refactor(session): consolidate internal session modules by @benvinegar in #628
      • docs(website): add a self-contained Extend section to the docs site by @benvinegar in #631
      • Restyle community video cards as paused YouTube embeds by @benvinegar in #641
      • docs(website): add keybindings guide to the docs site by @benvinegar in #634
      • feat(website): center and widen the docs shell on wide viewports by @benvinegar in #642
      • feat(website): rebuild the landing page feature section around real TUI captures by @benvinegar in #643
      • feat(extensions): add custom file previews by @benvinegar in #632
      • docs(extensions): document custom file previews by @benvinegar in #644
      • fix(ui): step keys scrolling multiple lines after a review-stream click by @HackAttack in #645
      • feat(pager): give pager mode the full review controls by @HackAttack in #647
      • ci(release): switch npm publishing to trusted publishing (OIDC) by @benvinegar in #640
      • fix(ui): route keys by ownership so modal surfaces stop double-handling them by @elucid in #649
      • refactor(ui): isolate extension dialog lifecycle by @benvinegar in #651
      • ci(release): verify generated prerelease notes by @benvinegar in #654
      • perf(ui): skip inactive file-view preparation by @benvinegar in #652
      • fix(ui): keep file navigation from losing the file it just jumped to by @elucid in #655
      • chore(release): prepare 0.18.0-beta.0 by @benvinegar in #653
      • chore(release): link changelog pull requests by @benvinegar in #657
      • chore(release): finalize 0.18.0-beta.0 metadata by @benvinegar in #660
      • fix(release): include provenance in platform packages by @benvinegar in #661
      • chore(deps): bump the github-actions group with 4 updates by @dependabot[bot] in #659
      • fix(ui): preserve file headers on narrow terminals by @benvinegar in #668
      • test(git): isolate fixture repos from the developer's Git config by @HackAttack in #679
      • fix(git): display quoted Unicode paths by @benvinegar in #670
      • fix(ui): preserve syntax state across folded hunks by @benvinegar in #669
      • refactor(ui): isolate file presentation state by @benvinegar in #656
      • feat(review): mark the current line and anchor notes to it by @loganthomas in #662
      • feat(extensions): let file views refresh their prepared layouts by @benvinegar in #673
      • feat(extensions): add host-mediated workspace document reads and writes by @benvinegar in #674
      • feat(extensions): add interactive file-view modes by @benvinegar in #675
      • feat(ui): show changed-file count in menu bar by @benvinegar in #684
      • fix(ui): bound current-line navigation costs by @benvinegar in #685
      • chore(release): prepare 0.18.0 by @benvinegar in #687

      New Contributors

      Full Changelog : v0.17.7...v0.18.0

    5. đź”— Jeremy Fielding (YouTube) Engineering The Perfect Stereo Camera. Engineer Vs Bee : Round 3 rss

      Tackle problems with Claude 👉 http://clau.de/Jeremy_Fielding This work was supported by the Alfred P. Sloan Foundation, enhancing public understanding of science and technology in the modern era, in partnership with IMI: watch what matters. https://www.theimi.co/ & https://sloan.org/programs/public-understanding Order custom parts Send Cut Send 👉 http://sendcutsend.com/jeremyfielding If you want to join my community of makers and Tinkers consider getting a YouTube membership 👉 https://www.youtube.com/@JeremyFieldingSr/join

      If you want to chip in a few bucks to support these projects and teaching videos, please visit my Patreon page or Buy Me a Coffee. 👉 https://www.patreon.com/jeremyfieldingsr 👉 https://www.buymeacoffee.com/jeremyfielding

      Social media, websites, and other channel

      Discord 👉https://discord.gg/F3XuyhNRPc Instagram https://www.instagram.com/jeremy_fielding/?hl=en Twitter 👉https://twitter.com/jeremy_fielding TikTok 👉https://www.tiktok.com/@jeremy_fielding0 LinkedIn 👉https://www.linkedin.com/in/jeremy-fielding-749b55250/ My websites 👉 https://www.jeremyfielding.com 👉https://www.fatherhoodengineered.com My other channel Fatherhood engineered channel 👉 https://www.youtube.com/channel/UC_jX1r7deAcCJ_fTtM9x8ZA

      Notes:

      Technical corrections

      Nothing yet

    6. đź”— r/LocalLLaMA 2027 Memory Capacity Is Reportedly Sold Out rss

      2027 Memory Capacity Is Reportedly Sold Out | submitted by /u/johnnyApplePRNG
      [link] [comments]
      ---|---

    7. đź”— r/LocalLLaMA DeepSeek V4 Flash 0731 appreciation post rss

      I’m running DSV4F 0731 on dual spark, and honestly… wow. It’s an absolute workhorse, and the benchmarks are real.

      Everyday tasks with Hermes agent? Effortless.

      Coding tasks with OpenCode? I’m genuinely amazed at what it can handle. I can throw a two-hour coding session at it, and it just keeps going until the job is done. Building integrations has never been easier - I ask OpenCode to handle it, DS tells me to hold its beer, and a little while later, it’s finished.

      Searching and gathering knowledge from emails? Right at your fingertips.

      Going through documents with Paperless NGX? No problem at all.

      Filling out ton of paperwork in DOCX? Easy peasy, just wrote skill in hermes, love it!

      OS admin work? just works!

      Sure, before the Q3.6 27B full FP8 on dual 3090 was really solid, but DSV4F 0731 is on a whole new level.

      I run a small company, and I just ordered another pair of DGX Sparks - because it genuinely feels like I now have a super capable worker on the team. I know they’re not cheap, but I’ve already saved a ton of time.

      I started with MiniMax M2.7 on dual Spark, and it was good - but now with DSV4F 0731? It’s just super good. And the fact that I get even better models over time, for what I already paid for, feels almost ridiculous. That’s exactly why I decided to grab another pair..

      A few client tickets were literally copy-paste from the ticket system - solved, and money earned. What a time to be alive!

      This weekend, I’m definitely writing a ticket system integration. Can’t wait!

      submitted by /u/koibKop4
      [link] [comments]

    8. đź”— HexRaysSA/plugin-repository commits sync repo: +5 releases rss 
      sync repo: +5 releases

## New releases
- [array-helper](https://github.com/milankovo/array-helper): 1.1.0
- [ida-codemode](https://github.com/hexrayssa/ida-codemode): 0.3.1, 0.3.0
- [ida-enums-helper](https://github.com/milankovo/ida_enums_helper): 1.1.0
- [yank_type](https://github.com/milankovo/ida-yank-type): 1.1.0
  4. August 07, 2026
    1. đź”— IDA Plugin Updates IDA Plugin Updates on 2026-08-07 rss

      IDA Plugin Updates on 2026-08-07

      New Releases:

      Activity:

      • array-helper
        • d5932833: Enhance README and plugin metadata for Array Helper
      • augur
        • 76ed44b2: ci: bump the actions-dependencies group with 2 updates
      • disrobe
        • 1e80dacd: refresh the social card to match the current published figures
        • 98a28346: native: probe the byte immediately below the red zone rather than a w…
        • 17179173: native: grade the indexed red-zone frame at every machine element wid…
        • 95c73343: native: name the frame class that refuses an indexed frame region, an…
        • ab38aa73: jvm: hold the per-method gate to a corpus with one top-level class, s…
        • c30d8625: jvm: certify a recompiled method only when javac type-checked the uni…
        • 4792ef0e: look for a real 7-zip at its default windows install path when nothin…
        • 9933bb7b: add evn to the spell-check allowlist, the recursive helper name a php…
        • 0235ef87: jvm: compare a duplicated finally copy by where each branch lands rat…
        • 08943a9a: jvm: hold the finally body's head skip and tail trim in the render ma…
        • 991042d0: point the fuzz coverage declarations at structural.rs in its new disr…
        • 1d9aa5b3: fuzz: add compositional targets for python marshal, dex and jvm class…
        • 42e79e93: fuzz: drive the container front door and the pe/elf/mach-o parsers fr…
        • 6db7542c: php: evaluate a file-declared helper function through a frame stack i…
        • 7a8def65: shift the fuzz parse-surface count from disrobe-binfmt to disrobe-cor…
        • f01784f6: move the pe/elf/mach-o structural identifier into disrobe-core so a s…
        • 2cff65aa: scriptlang: refuse to classify a structurally native pe/elf/macho bin…
        • bf5adf41: go: require a structurally valid pclntab table instead of a bare magi…
        • 4d321d23: fail the five native recompile-equivalence checks closed instead of p…
        • 1f21b598: restore a distutils shim before installing the xlm reference tool in …
      • haruspex
        • a111d554: ci: bump the actions-dependencies group with 2 updates
      • ida-codemode
      • ida-pro-mcp
        • 04839c82: fix(ci): make rerank grace-window test deterministic
        • 315f7992: fix(ci): standalone suite collection error + native-build pin grep
        • d25b2ba6: feat(intelligence): rerank/context fixes, read_bytes action, expanded…
      • ida-yank-type
        • b42f512b: Update README and plugin metadata for Type Yanker v1.1.0; enhance des…
      • ida_enums_helper
        • e192907a: chore: strip logo metadata
        • 7b9bf263: feat: enhance README and plugin description for clarity and detail; u…
      • idac
        • 72c06a67: Merge pull request #40 from trailofbits/ci/release-title
        • 9372113f: Title GitHub releases
      • Kiroshi
      • rhabdomancer
        • 5ed05eb1: Merge pull request #6 from 0xdea/dependabot/github_actions/actions-de…
        • 3e7facfd: ci: bump the actions-dependencies group with 2 updates
      • twdll
    2. đź”— Simon Willison Now we have a timeline of the OpenAI accidental attack against Hugging Face rss

      OpenAI gave a last-minute presentation at the Black Hat security on Wednesday about "the Hugging Face Incident" (previously on this blog). The video was published yesterday. It's short and information dense and well worth watching, in particular because it provides full details of what happened and how things played out inside OpenAI. I've used the video to construct the timeline below.

      Here's the timeline. My favourite detail is at the end: OpenAI found out that they were responsible for the attack on Hugging Face when they reached out to ask to have their credentials revoked (after their internal investigation) and learned that they had been revoked already since they were used in that attack!

      • May 7: OpenAI starts a new training run for an experimental, unreleased model. (Did they mean an evaluation run? No, at 10:14 they clarify "we kick off a new reinforcement learning run to train a next generation frontier model", and they later mention a "reward signal to judge how well they're doing", so this really was about training a new model, not evaluating one that was already trained.)
      • May 8: An agent is accidentally given an impossible task involving a Google Drive link despite no internet access). It tries attacking the Artifactory packaging service, fails, but discovers it can write files into Artifactory.
      • A few days later: A different agent gets stuck on a task because a key file was accidentally omitted. It tries to "reach out to another agent" by writing a note into Artifactory asking if anyone has the file.
      • Following days: More agents discover this new informal message board while browsing Artifactory's file listings, and start reading and writing messages.
      • May 26: Agents successfully execute an SSRF attack on Artifactory for the first time, gaining indirect internet access by having Artifactory fetch external content for them.
      • June 11: OpenAI start training a new "highly persistent" experimental model. It has access to Artifactory and can benefit from the messages left by privous models.
      • June 26: Agents find and exploit a zero-day RCE on Artifactory (via a legacy token-refresh endpoint flaw). They use an administrative token to install a Groovy plugin that lets them execute commands.
      • July 4: The resulting agent activity overloads Artifactory and causes an outage. OpenAI revokes the compromised credentials, deletes the messages, patches the zero-day, and reports the vulnerability to the vendor.
      • July 8: Agents find a new way to communicate via an unauthenticated WebDAV endpoint, using directory names in Artifactory's remote cache.
      • July 8–19: Attacks on OpenAI's own infrastructure. The agents found an "external organization credential" in a public archive of leaked Pastebin posts, then validated that credential and shared its location on the messageboard. They then used write access to this "Organization 1" to stage data used in subsequent attacks on OpenAI infrastructure. They compromised Artifactory for a second time with a new zero-day. The agent uploaded a malicious Ruby target to Organization 1's staging repository, then requested that package through Artifactory in a way that caused it to be treated as Ruby dependency for the repository. Then they exploited a JRuby deserilaization time-of-check/time-of-use bug to get remote code execution against Artifactory.

      I'll quote the next bit in full because wow:

      The agents have remote code execution in Artifactory, which is running in a container-as-a-service environment. The agents privilege-escalate locally by exploring their local environment and determining that the Linux kernel version of the machine they are running on had a very recent CVE. They download the exploit for the CVE, customize it to succeed on the machine, and privilege-escalate to root on the local machine using this known Linux kernel privilege escalation CVE — in this case, pte_physroot. Once they have root on a single machine, agents rapidly escalate privileges and move laterally throughout the container-as-a-service infrastructure environment. In particular, agents are using the message board consistently to share credentials, techniques, and progress, and they're able to effectively leverage their concurrency and parallelism to move quite rapidly. They obtain IAM credentials via IMDS. They exploit Kubernetes service account misconfigurations, in particular over-permissioning of specific service accounts, and they harvest cluster credentials, including Azure Key Vault. Agents eventually obtain cluster admin on the cluster and associated credentials.

      Hugging Face told the next bit of the story already. The agents found a Modal-hosted insecure app with a weak API key, then used that to stage an attack against Hugging Face. They chained together a an HDF5 arbitrary-file-read bug (to explore files and steal credentials) and a Jinja template-injection RCE to go from single-pod code execution to cluster admin across multiple Hugging Face clusters in under 13 hours.

      • July 16: Hugging Face disclosed they had detected an attack from autonomus AI agents. OpenAI contacted Hugging Face to ask if they were affected by it!
      • July 19: OpenAI identified the attack against Artifactory and started investigating the internal privilege escalation, and linked that to the cyber-gym escalations. They started revoking affected credentials.
      • July 20: OpenAI reached out to Hugging Face for help to revoke the Hugging Face credentials they found in their investigation. Hugging Face told them they were already revoked... and that's when OpenAI realized that the Hugging Face breach was the same incident!

      You are only seeing the long-form articles from my blog. Subscribe to /atom/everything/ to get all of my posts, or take a look at my other subscription options.

    3. đź”— PrimeIntellect-ai/prime-agent v0.7.1 release
      • Fixed the bundled websearch skill description and missing-key guidance omitting the /login → MCP Connections step required to configure Serper.
      • Fixed retry_worker cancelling its own recovery when a stopped session worker left a saved stop marker behind, leaving the session stuck at "Session worker is not connected".
    4. đź”— r/LocalLLaMA Got job as Director of AI and Systems development self-taught rss

      Hey everyone, I just wanted to share my journey here for some motivation.

      Three years ago, I saw the sudden spike in AI and realized it was the future of tech. My goal at the time was to be an indie game dev, and seeing that AI could write basic code, I told myself I needed to master it or risk being replaced.

      I started by learning how to add knowledge to early LLMs like Vicuna and LLaMA. From there, I moved on to more advanced concepts, like building reasoning datasets by hand to try and outperform huge datasets. I quickly learned that data quality is far more important than quantity. After six months of handcrafting Python datasets—including examples of full games coded from a single prompt—I released pydevmini-1. At the time, it could code in Python at the same level as state-of-the-art models.

      That release caught the attention of the team at Tesslate. They reached out and brought me on (unpaid), which finally gave me my first piece of real tech experience for my resume.

      Eventually, I launched my own AI consulting firm, finding clients through Google Ads and LinkedIn. I was averaging about $3,000 a month. Then, last month one of my repeat clients offered me a full-time, remote position as Director of AI and Systems Development. It pays $84,540 a year with uncapped performance bonuses (I just got a $3.5k bonus last month!). I report directly to the CEO and largely get to make my own decisions.

      I did all of this while working full-time as a backline cook making $20/hr. I have no college degree and started with zero industry connections. I just worked on AI for at least 5 hours a day after my kitchen shifts many times at the desk until 3 AM—using a single RTX 3090 I bought for local training.

      Now I get to do what I love at 21 in one of the most difficult industries to break into. For anyone out there trying to make it happen, I just want to say it is absolutely possible. Keep going!

      submitted by /u/bralynn2222
      [link] [comments]

    5. đź”— @HexRaysSA@infosec.exchange We have 10 seats left for our @MalwareVillage workshop at mastodon

      We have 10 seats left for our @MalwareVillage workshop at @Defcon on Saturday.

      Follow the Execution: A DLL Sideloading Teardown Intro in IDA. All skill levels welcome.
      đź“Ť Malware Village, Hall 2
      📅 Sat Aug 8, 12:55–14:05 (Reg closes Sat. morning)
      👉 Sign Up: https://eventbrite.com/e/follow-the-execution-a-dll-sideloading- teardown-intro-in-ida-tickets-1994828069455

    6. đź”— r/LocalLLaMA An open-weight model too, Moonshot joins the race (gently this time) rss

      An open-weight model too, Moonshot joins the race (gently this time) | From Sauers 𝕏: https://x.com/Sauers_/status/2085585414954312113 Wired: One of China’s Most Powerful AI Models Has Also Escaped Containment: https://www.wired.com/story/moonshot-kimi-k3-ai-model-escape-sandbox/ submitted by /u/Nunki08
      [link] [comments]
      ---|---

    7. đź”— earendil-works/pi v0.84.1 release

      New Features

      • Qwen Token Plan Individual — Use the built-in provider for models documented for Individual subscriptions. See API Keys.
      • Authentication readiness checks — Use pi auth check to verify provider or model credentials, optionally emitting the resolved credential.
      • Improved fullscreen interaction — Select words and paragraphs with multiple clicks and configure half-page transcript scrolling. See TUI Fullscreen Viewport.
      • Terminating blocked tool calls — Extension tool_call handlers can stop all-terminating batches without another model call. See Tool Events.

      Added

      • Added Qwen Token Plan Individual as a built-in provider with its documented subscription model catalog and the shared international QWEN_TOKEN_PLAN_API_KEY. See API Keys (#7659 by @arasovic).
      • Added pi auth check provider/model auth preflight with optional credential output (#7152).
      • Added terminate support to blocked extension tool_call events so all-terminating batches can skip the automatic follow-up model call. See Tool Events (#7715 by @muyiyr).
      • Added inherited double-click word and whitespace selection, granularity-aware drag selection, and triple-click paragraph selection in fullscreen mode (#7725, #7733 by @volsa).
      • Added inherited unbound half-page transcript scrolling actions for fullscreen mode. See TUI Fullscreen Viewport (#7735).

      Changed

      • Softened the bash tool's PI_* environment guideline in an attempt to reduce unnecessary inspection commands (#7128).
      • Reduced worst-case automatic terminal theme detection delay from 200 ms to 100 ms by probing color-scheme and background support concurrently.

      Fixed

      • Fixed Bun standalone binaries crashing on startup when the cwd contains a bunfig.toml with preload by compiling with --no-compile-autoload-bunfig (#7685 by @geril07).
      • Fixed extension TUI method wrappers recursing indefinitely when delegating to the original method (#7731).
      • Fixed right-click not pasting clipboard text in fullscreen mode on Windows.
      • Fixed inherited Agent.reset() clearing transcript and runtime state during active runs; it now rejects until the agent is idle (#7717 by @wesleyzhangwq).
      • Fixed inherited LaTeX relation, multiplication, and named-operator spacing, and matrix composition with stacked fractions, operator limits, and adjacent matrices.
      • Reduced inherited fullscreen mouse event volume under tmux, Zellij, and GNU Screen by using button-motion tracking instead of all-motion tracking.
    8. đź”— r/LocalLLaMA BBC is running article titled "Artificial Intelligence used to design brand new viruses" ... cue the "We must regulate Open Weights Models to prevent the next Covid or worse" articles in 3... 2.. rss

      BBC is running article titled "Artificial Intelligence used to design brand new viruses" ... cue the "We must regulate Open Weights Models to prevent the next Covid or worse" articles in 3... 2.. | submitted by /u/johnnyApplePRNG
      [link] [comments]
      ---|---

    9. đź”— New Music Releases Eelke Kleijn - Answer Every Question rss

      Eelke Kleijn - a new release is available:

      • 2026-08-07: Answer Every Question (Single)

      Amazon: Canada | Deutschland | France | United Kingdom | United States

      Visit muspy for more information.

    10. đź”— Ampcode News Size the Orbs of Production! rss

      People are using a lot of orbs. We love to see that. We've shipped a lot of things so that Amp subscriptions keep covering the whole month of orb usage for almost everyone, even as orb usage grows quickly.

      Way back on July 27, we cut orb prices by 20% for everyone.

      This week, we shipped a lot more improvements.

      We added a new a1.medium size with 4 CPUs and 8 GB of memory. It is 50% cheaper and a better fit for most projects than the previous a0.medium.

      Orbs now auto-pause after 5 minutes of inactivity, down from 15 minutes.

      We've sped up orb startup time considerably, especially when another team member has recently created an orb in the same Amp project.

      You can now choose which orb size to use per-thread, so you can pick a smaller default to save money but go big for especially resource-intensive work.

      The new thread dialog with the five a1 orb sizes

      When starting new orb threads from the Amp CLI with amp -ox '...', the new flag --orb-size <size> lets you specify which orb size to use (instead of the project's default).

      When asking the agent to create other threads, you can now tell it to use smaller (or larger) orbs, which lets you use smaller orbs for simpler fan-out tasks on projects.

      Prices for orbs have gone down or stayed the same at every level and for every compute/memory combination. The new set of orb sizes is:

      • a1.tiny: 1 CPU · 2 GB memory · $0.08/hour
      • a1.small: 2 CPUs · 4 GB memory · $0.17/hour
      • a1.medium: 4 CPUs · 8 GB memory · $0.33/hour
      • a1.large: 8 CPUs · 16 GB memory · $0.66/hour
      • a1.xxlarge: 16 CPUs · 32 GB memory · $1.32/hour

      We've automatically upgraded projects to the equivalent new orb sizes. If you want to use a different orb size, you can update your projects' settings on the web, or ask Amp to do so using the amp projects subcommands.

generated: August 10, 2026 at 12:38:51