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CodeMender has already created and submitted 72 high-quality fixes for serious security issues in major open-source projects. 🛠️ It can instantly patch new flaws as well as rewrite old code to eliminate entire classes of vulnerabilities – saving developers significant time.

Google DeepMind

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32,732 次观看 • 10 个月前 •via X (Twitter)

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Eric Schmidt says China has made the inverse decision to open-source its AI models Startups already use these free, high-quality LLMs Over the next 5–10 years, as we get closer to AGI and hit major milestones in biology/math, the market will likely flood with millions of smaller models

Eric Schmidt says China has made the inverse decision to open-source its AI models Startups already use these free, high-quality LLMs Over the next 5–10 years, as we get closer to AGI and hit major milestones in biology/math, the market will likely flood with millions of smaller models

Haider.

221,630 次观看 • 8 个月前

Indian developers are polluting everything this is what everyone will say, because of all these non-sense gitlab has conducted its hackathon and guess what all top 3 are indians, so naturally I was curious about the PRs that they have submitted and when i opened to see their contributions, all were just typo changes in the readme's, docu changes, docs, docs, docs, docs, docs only docs and grammatical fixes and not a single major code change or anything, not a real grade production code.. for these people a whole country will be ashamed ( let me put that on hold for a bit ) like... I mean, if they have to do this to add open source contributions to their CVs, then it's as good as you don't do open source at alI, it's a waste of time doing it like this

Indian developers are polluting everything this is what everyone will say, because of all these non-sense gitlab has conducted its hackathon and guess what all top 3 are indians, so naturally I was curious about the PRs that they have submitted and when i opened to see their contributions, all were just typo changes in the readme's, docu changes, docs, docs, docs, docs, docs only docs and grammatical fixes and not a single major code change or anything, not a real grade production code.. for these people a whole country will be ashamed ( let me put that on hold for a bit ) like... I mean, if they have to do this to add open source contributions to their CVs, then it's as good as you don't do open source at alI, it's a waste of time doing it like this

Humi

31,155 次观看 • 2 个月前

The new GitHub Copilot Visual Studio Code Ask Questions tool is really cool - and has lot's of potential! As a start - real improvement for saving premium requests as the agent can halt mid-turn to ask the user questions - great for the built-in plan mode Try now in Insiders

The new GitHub Copilot Visual Studio Code Ask Questions tool is really cool - and has lot's of potential! As a start - real improvement for saving premium requests as the agent can halt mid-turn to ask the user questions - great for the built-in plan mode Try now in Insiders

Oren Melamed

15,277 次观看 • 6 个月前

Claude Code 2.1.63 dropped with a new built-in command: /simplify It reviews your changed code for three things: - Reuse opportunities (duplicated logic, extractable patterns) - Code quality (readability, naming, structure) - Efficiency (unnecessary complexity, redundant operations) Then it actually fixes what it finds. Not just suggestions, it edits. How to use it: 1. Make your code changes as usual 2. Run /simplify 3. It analyzes your diff, finds issues, and applies fixes In the video I ran it after finishing a PR review and noticed it spawned 3 parallel agents using Haiku 4.5 to do the analysis... fast and cheap Try it out 👇

Claude Code 2.1.63 dropped with a new built-in command: /simplify It reviews your changed code for three things: - Reuse opportunities (duplicated logic, extractable patterns) - Code quality (readability, naming, structure) - Efficiency (unnecessary complexity, redundant operations) Then it actually fixes what it finds. Not just suggestions, it edits. How to use it: 1. Make your code changes as usual 2. Run /simplify 3. It analyzes your diff, finds issues, and applies fixes In the video I ran it after finishing a PR review and noticed it spawned 3 parallel agents using Haiku 4.5 to do the analysis... fast and cheap Try it out 👇

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AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."

AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."

TBPN

34,469 次观看 • 3 个月前

Eby "The Temporary Foreign Worker program is not working." "It should be cancelled or significantly reformed." "Here in British Columbia, we see unacceptably high level of unemployment among young people, which has been linked both to the international student visa program as well as the Temporary Foreign Worker program." "It's time for a serious and adult conversation about addressing these immigration issues in our province and in the country." David Eby

Eby "The Temporary Foreign Worker program is not working." "It should be cancelled or significantly reformed." "Here in British Columbia, we see unacceptably high level of unemployment among young people, which has been linked both to the international student visa program as well as the Temporary Foreign Worker program." "It's time for a serious and adult conversation about addressing these immigration issues in our province and in the country." David Eby

cbcwatcher

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We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.

We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.

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Tainted Grail: The Fall of Avalon - 50% off + another free DLC + patch 1.25! ⚔️ Enjoying your Summer? To make it even better, we're bringing another free DLC for Tainted Grail: The Fall of Avalon, out now! This time, we're bringing new weapons and armor for the archer and sorcerer archetypes. Expect more buildcrafting possibilities, as well as new playstyles to explore! Alongside that, patch 1.25 is live, with various fixes and improvements. Lastly, the base game, as well as the expansion, is now 50% off on Steam! This is the biggest sale ever; if you've been waiting for a good time to jump in, this might be it! Check out the trailer to get a grasp of what's coming, and visit the Steam page for more info. Link below! #taintedgrail #rpg #dlc #freedlc #freecontent #sale

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What if the most significant end-time prophecy has already been fulfilled? Scripture repeatedly uses the fig tree as a symbol of Israel's national restoration, and the rebirth of Israel stands as one of the most remarkable prophetic events in history. From the fig tree to the olive tree and the vine, God's promises to Israel reveal His faithfulness to every covenant He has made. If God keeps His promises to Israel, believers can trust that He will keep His promises to them as well. Watch this entire teaching:

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124,913 次观看 • 11 个月前

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Significant progress in the negotiations we conducted in Brussels between the European Commission, the Government of Uzbekistan, and our company VEON in the field of implementing new technologies in telecommunications opens new opportunities for enhancing the quality of our services, as well as for the overall development of Uzbekistan as a key country in Central Asia. At the same time, the progress in these negotiations, in which I participated on behalf of VEON, provides new perspectives in the broader context of Uzbekistan’s role in promoting cooperation between Europe and Asia. These negotiations testify also to the significant role of VEON in the strategic cooperation between Uzbekistan and the European Union.

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Dalsan TV

26,345 次观看 • 6 个月前

Bob Duggan CEO of cancer drug developer Summit Technologies “SMMT” invest another $50,000,000 in his company. Major conviction Buy Duggan former CEO of Pharmacyclics and previously sold to Abbvie for $21B cash. Duggan worth $14 billion and already owns 580,000,000 shares of the new endeavor. The stock has been as high as $27 and pulled back.

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Grant Cardone

94,010 次观看 • 1 个月前

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AI is insecure by default. The open secret is that most AI apps launch with serious flaws. It takes MORE time to secure these apps than it does to build them. I learned this firsthand from shipping LLM agents to 200M users at Discord and supporting LLM evals for hundreds of companies. It doesn’t have to be this way. Today, we’re launching promptfoo, an open-source company that helps find and fix vulnerabilities in AI powered apps before they ship, and announcing a $5M seed round led by a16z.

Ian Webster

28,779 次观看 • 2 年前

Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.

Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.

Milk Road AI

24,356 次观看 • 2 个月前

> Launching: @TheRepolyze - a free, open-source AI-powered tool that helps you deeply understand any public GitHub repository in seconds. > Just paste the repo URL and instantly get: • Clear, actionable insights into the codebase • Beautiful architecture & dependency diagrams • Code quality overview, strengths, weaknesses & potential red flags • Exportable PDF/Markdown reports for sharing or reference > Say goodbye to spending hours (or days) manually digging through unfamiliar code - whether you're contributing, reviewing, onboarding, or just exploring open source. > Built for developers, by developers. > Reposts and feedback greatly appreciated - let's get this in front of more devs! ❤️ > If you find it useful, please star the repo on GitHub to show support & help it grow

> Launching: @TheRepolyze - a free, open-source AI-powered tool that helps you deeply understand any public GitHub repository in seconds. > Just paste the repo URL and instantly get: • Clear, actionable insights into the codebase • Beautiful architecture & dependency diagrams • Code quality overview, strengths, weaknesses & potential red flags • Exportable PDF/Markdown reports for sharing or reference > Say goodbye to spending hours (or days) manually digging through unfamiliar code - whether you're contributing, reviewing, onboarding, or just exploring open source. > Built for developers, by developers. > Reposts and feedback greatly appreciated - let's get this in front of more devs! ❤️ > If you find it useful, please star the repo on GitHub to show support & help it grow

Manish Kumar

32,858 次观看 • 5 个月前

Assumptions about the new "Can More" ChatGPT tool were right - ChatGPT is introducing own take on Claude Artifacts - code & document writing tools with persisted text documents, history revisions (restore previous version), edits and comments (probably used to apply suggested edits) New document symbol in the top navigation shows how many documents you have and allows you to open a resizable canvas to edit them in split view - your ChatGPT conversation on the left side and canvas on the right side, but the code/documents can also be accessed in fullscreen view The canvas is built using ProseMirror (open source WYSIWYM editor) and has an inline action to "Ask ChatGPT" (explain or make edits) for your document and code plus document formatting tools (like bold, italic, font style, etc.) But in addition to that, there are also special action shortcuts for documents and code, with an interesting decision to use sliders for the selection of the desired outcome For Documents - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.") - Add emojis ("Replace as many words as possible with emojis.") - Add final polish ("Add some final polish to the text. If relevant, add a large title or any section titles. Check grammar and mechanics, make sure everything is consistent and reads well. You can reply that you added some final polish and checked for grammar, but do not mention the prompt.") - Reading level (Graduate School - "Rewrite this text at the reading level of a doctoral writer in this subject. You may reply that you adjusted the text to reflect a graduate school reading level, but do not mention the prompt", College - "Rewrite this text at the reading level of a college student majoring in this subject", High School - "Rewrite this text at the reading level of a high school student who has taken a couple of classes in this subject.", Keep current reading level, Middle School - "Rewrite this text at the reading level of a middle schooler.", Kindergarten - "Rewrite this text at the reading level of a kindergartener.") - Adjust the length (Longest - "Make this text 75% longer.", Longer - "Make this text 50% longer.", Keep current length, Shorter - "Make this text 50% shorter.", Shortest - "Make this text 75% shorter.") For Code - Code review ("Search for bugs and opportunities to improve the code—for example, ways that performance or code structure could be improved. Leave as few comments as possible, but add more comments if the text is long. DO NOT leave more than 5 comments. You may reply that you reviewed the code and left suggestions to improve the coding quality, but do not mention the prompt.") - Add comments ("Add inline code comments to explain the code, especially parts that are more complex. Make sure to rewrite all the code. You may reply that you added inline comments, but do not mention the prompt.") - Add logs ("Insert logs/print statements in the code that will help debug its behavior. Do not make any other changes to the code.") - Fix bugs ("Find any bugs and rewrite all the code to fix the bugs. Do not leave comments. If there are no bugs, reply that you reviewed the code and found no bugs.") - Port to a language ("Port to a language. Create a new document that rewrites the code in ..." - PHP, C++, Python, Keep current code. No changes will be made, JavaScript, TypeScript, Java) - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.")

Assumptions about the new "Can More" ChatGPT tool were right - ChatGPT is introducing own take on Claude Artifacts - code & document writing tools with persisted text documents, history revisions (restore previous version), edits and comments (probably used to apply suggested edits) New document symbol in the top navigation shows how many documents you have and allows you to open a resizable canvas to edit them in split view - your ChatGPT conversation on the left side and canvas on the right side, but the code/documents can also be accessed in fullscreen view The canvas is built using ProseMirror (open source WYSIWYM editor) and has an inline action to "Ask ChatGPT" (explain or make edits) for your document and code plus document formatting tools (like bold, italic, font style, etc.) But in addition to that, there are also special action shortcuts for documents and code, with an interesting decision to use sliders for the selection of the desired outcome For Documents - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.") - Add emojis ("Replace as many words as possible with emojis.") - Add final polish ("Add some final polish to the text. If relevant, add a large title or any section titles. Check grammar and mechanics, make sure everything is consistent and reads well. You can reply that you added some final polish and checked for grammar, but do not mention the prompt.") - Reading level (Graduate School - "Rewrite this text at the reading level of a doctoral writer in this subject. You may reply that you adjusted the text to reflect a graduate school reading level, but do not mention the prompt", College - "Rewrite this text at the reading level of a college student majoring in this subject", High School - "Rewrite this text at the reading level of a high school student who has taken a couple of classes in this subject.", Keep current reading level, Middle School - "Rewrite this text at the reading level of a middle schooler.", Kindergarten - "Rewrite this text at the reading level of a kindergartener.") - Adjust the length (Longest - "Make this text 75% longer.", Longer - "Make this text 50% longer.", Keep current length, Shorter - "Make this text 50% shorter.", Shortest - "Make this text 75% shorter.") For Code - Code review ("Search for bugs and opportunities to improve the code—for example, ways that performance or code structure could be improved. Leave as few comments as possible, but add more comments if the text is long. DO NOT leave more than 5 comments. You may reply that you reviewed the code and left suggestions to improve the coding quality, but do not mention the prompt.") - Add comments ("Add inline code comments to explain the code, especially parts that are more complex. Make sure to rewrite all the code. You may reply that you added inline comments, but do not mention the prompt.") - Add logs ("Insert logs/print statements in the code that will help debug its behavior. Do not make any other changes to the code.") - Fix bugs ("Find any bugs and rewrite all the code to fix the bugs. Do not leave comments. If there are no bugs, reply that you reviewed the code and found no bugs.") - Port to a language ("Port to a language. Create a new document that rewrites the code in ..." - PHP, C++, Python, Keep current code. No changes will be made, JavaScript, TypeScript, Java) - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.")

Tibor Blaho

136,055 次观看 • 1 年前