🚀 AI Model Updates
Pentest reports full of unverified alerts are noise, not signal. Xalgorix @xalgorix runs a 22-phase autonomous offensive methodology and re-exploits every finding before it hits the report. Only proven vulns make the cut.
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Xalgorix's 22-phase methodology: Xalgorix's approach involves a 22-phase autonomous offensive methodology that re-exploits every finding before it hits the report, ensuring only proven vulnerabilities make the cut.
Reducing noise in pentest reports: By using Xalgorix's methodology, pentest reports can be reduced to only include verified vulnerabilities, making it easier for developers to focus on fixing the most critical issues.
Integration with CI/CD pipeline: Xalgorix's methodology can be integrated into a CI/CD pipeline to ensure that only verified vulnerabilities are reported, making it easier to prioritize and fix issues.
🔗 Resources:
- Original source ↗
- Original source
- Xalgorix
- Xalgorix's 22-phase autonomous offensive methodology for reducing noise in pentest reports
🤖 Multimodal Decision Model
We turned Qwen3.8-27B into a multimodal decision model. It beat Pokémon FireRed’s elite four and champion with sub-100 ms decisions from live game state. With SGLang’s native /v1/decisions, you can now turn LLMs and VLMs into classification and scoring models.
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Qwen3.8-27B multimodal decision model: Qwen3.8-27B was turned into a multimodal decision model that can make decisions in sub-100 ms from live game state, beating Pokémon FireRed’s elite four and champion.
SGLang’s native /v1/decisions: SGLang’s native /v1/decisions API allows users to turn LLMs and VLMs into classification and scoring models, enabling multimodal decision-making.
Advantages of multimodal decision models: Multimodal decision models can provide faster and more accurate decisions, making them suitable for applications that require real-time decision-making.
🔗 Resources:
- Original source ↗
- Original source
- SGLang
- SGLang’s native /v1/decisions API for turning LLMs and VLMs into classification and scoring models
📅 Community Lunch
Community Lunch + Ω Labs Coworking Lunch with people of Montréal's AI safety and governance community, then an afternoon of coworking. Bring your own lunch and your laptop. Thursday Oct 1st, 12:30 to 4:30 PM, at Ω Labs (3813 St-Denis).
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Community Lunch and Coworking: The event will feature a community lunch and coworking session with people from Montréal's AI safety and governance community.
Date and Time: The event will take place on Thursday, October 1st, from 12:30 to 4:30 PM.
Location: The event will be held at Ω Labs, located at 3813 St-Denis.
🔗 Resources:
- Original source ↗
- Original source
- Ω Labs
- Ω Labs Coworking Space
🚀 Career Rewired for the AI Age
On Sept. 17, we packed a room with builders, founders, and operators at our event, Career Rewired for the AI Age, with @EmergencesLabs . One thing kept coming up: being “AI native” is about much more than prompting. It’s being able to define a problem, use AI to move it forward,
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Career Rewired for the AI Age: The event focused on how to adapt to the changing landscape of work in the AI age.
Being “AI native”: Being “AI native” is not just about using AI tools, but also about being able to define problems and use AI to move them forward.
Importance of defining problems: Defining problems is a crucial skill in the AI age, as it allows individuals to identify areas where AI can be used to drive progress.
🔗 Resources:
- Original source ↗
- Original source
- @EmergencesLabs
- Career Rewired for the AI Age
🚀 GPT-6.1 Sol
GPT-6.1 Sol has just launched and we've made it our new default model for new agents in Autohive. It's cheaper to run and extremely clever. Don't worry, all your existing agents keep the model you chose, and you can switch any agent over in its settings.
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GPT-6.1 Sol: GPT-6.1 Sol is a new AI model that has been made the default model for new agents in Autohive.
Cost savings: GPT-6.1 Sol is cheaper to run than previous models.
Switching to GPT-6.1 Sol: Existing agents can be switched to use GPT-6.1 Sol by changing their settings.
🔗 Resources:
- Original source ↗
- Original source
- Autohive
- GPT-6.1 Sol
🚀 Scaling Backend Resources
Your app shouldn’t outgrow its backend MeDo Pro and Max users can now scale @Supabase backend resources from Low to Ultra directly in the editor — giving production apps, growing traffic, and more demanding workloads the room they need. No more building around a fixed
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Scaling backend resources: MeDo Pro and Max users can now scale @Supabase backend resources from Low to Ultra directly in the editor.
Benefits of scaling: Scaling backend resources can provide more room for production apps, growing traffic, and more demanding workloads.
No need to build around fixed resources: With the ability to scale backend resources, there is no need to build around fixed resources.
🔗 Resources:
- Original source ↗
- Original source
- @Supabase
- MeDo Pro and Max
🚀 Batching, Weight Sharding, and KV Cache Traffic
you'll know more about batching, weight sharding, and KV cache traffic than 99.92% of people if you fully understand this paper follow and save to keep up with wafer ai performance engineering series
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Wafer AI performance engineering series: The paper is part of the Wafer AI performance engineering series.
Batching, weight sharding, and KV cache traffic: The paper covers the topics of batching, weight sharding, and KV cache traffic.
Importance of understanding these topics: Understanding these topics can provide a significant advantage in performance engineering.
🔗 Resources:
- Original source ↗
- Original source
- Wafer AI
- Wafer AI performance engineering series
🚀 FLUX Models
We'll be joined live by the @bfl_ai team on Friday to chat through the latest in FLUX models, including FLUX 3 Video Generation and their open source FLUX 3 Action 7B model Come hang out with your Friday morning coffee at 10am PT
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FLUX models: The @bfl_ai team will be discussing the latest developments in FLUX models.
FLUX 3 Video Generation: FLUX 3 Video Generation is one of the topics that will be covered.
Open source FLUX 3 Action 7B model: The team will also be discussing their open source FLUX 3 Action 7B model.
🔗 Resources:
- Original source ↗
- Original source
- @bfl_ai
- FLUX models
🚀 Snapshot System
our explainer of our snapshot system didn't get much attention but it is quite significant in reality solves most of the pain points serious sandbox users have with sandboxes reliable, effortless snapshots are amongst the top things u should look for, we learned it thru pain
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Snapshot system: The snapshot system is a significant feature that solves many pain points for serious sandbox users.
Reliable and effortless snapshots: The system provides reliable and effortless snapshots, which are essential for sandbox users.
Importance of snapshots: Snapshots are crucial for sandbox users, and the snapshot system addresses many of the pain points associated with them.
🔗 Resources:
- Original source ↗
- Original source
- AniC_dev
- Snapshot system
🚀 AI Sandbox Product
our AI sandbox product, https:// boat.dev is growing amazingly fast now with users reporting they're picking us despite considering E2B, Daytona, Modal, Blaxel, Namespace and having strict requirements feels great to see our product improve & mature let's keep pushing!!
Key Points:
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AI sandbox product: The AI sandbox product, https:// boat.dev, is growing rapidly.
Competitive landscape: The product is being considered by users who are also evaluating other options, such as E2B, Daytona, Modal, Blaxel, and Namespace.
Importance of meeting strict requirements: The product must meet strict requirements to be competitive in the market.
🔗 Resources:
- Original source ↗
- Original source
- AniC_dev
- AI sandbox product
