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#aiml — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #aiml, aggregated by home.social.

  1. We’re currently recruiting a Research Software Engineer or Senior Research Software Engineer to join the KDL team at King’s.

    Our team works closely with researchers and partners across disciplines, particularly in the arts and humanities, developing thoughtful, impactful digital research projects. We’re looking for someone who enjoys collaborative, applied work at the intersection of research and technology.

    The position is full-time with an indefinite contract.

    More details here:
    kcl.ac.uk/jobs/145925-research

    Please share within your networks if relevant.

    #DigitalHumanities #rse #dh #softwaredeveloper #softwareengineer #RSEng #aiml #digitalcreativity #immersiveXR #datavisualisation #indigenousdh #devops

    @ResearchSoftEng @kingsartshums @kingsdh @uk_ie_dh

  2. A Very Specific Point About Those Who Claim To Make Artwork With AI Commissioning is not the same thing as creating. Archive: ia: https://s.faithcollapsing.com/va5wy https://s.faithcollapsing.com/ol7rq#writing #ai #ai-ml #art #visual-arts

  3. In the Old Days (2003-2004), a guy in the US called Julian Bleecker developed a portable WiFi node called wifi.bedouin which he toted around in a backpack. I was enthralled! Imagine being able to do that! I felt I'd like to do the same but I had very little money, lived in the UK and wasn't at Uni. Even so, I had a go, and my version - "Billy Nomad/YARWAP" was born. YARWAP=Yet Another Roaming Wireless Access Point ☺️

    I wrote it up as I went along and today rediscovered the PDF, which is available for you reading pleasure at petergarner.net/projects/YARWA and Julian's is at nearfuturelaboratory.com/proje

    I did actually take it outside a couple of times for testing, but in those days so few people had mobile devices that did WiFi, that it didn't really achieve its objective. Enjoy!

    #roaming #wifi #MobileComputing #Freebsd #AIML

  4. Check out ˗ˏˋ ⭒ lnkd.in/gE2wUqgc ⭒ ˎˊ˗ to see my intro whilst you listen.

    I'm thus re-naming this work as "CVE Keeper - Security at x+1; rethinking vulnerability management beyond CVSS & scanners". I must also thank @andrewpollock for reviewing several of my verbose drafts. 🫡

    So, Security at x+1; rethinking vulnerability management beyond CVSS & scanners -

    Most vulnerability tooling today is optimized for disclosure and alert volume, not for making correct decisions on real systems. CVEs arrive faster than teams can evaluate them, scores are generic, context arrives late, and we still struggle to answer the only question that matters: does this actually put my system at risk right now?

    Over the last few years working close to CVE lifecycle automation, I’ve been designing an open architecture that treats vulnerability management as a continuous, system-specific reasoning problem rather than a static scoring task. The goal is to assess impact on the same day for 0-days using minimal upstream data, refine accuracy over time as context improves, reason across dependencies and compound vulnerabilities, and couple automation with explicit human verification instead of replacing it.

    This work explores:

    ⤇ 1• Same-day triage of newly disclosed and 0-day vulnerabilities
    ⤇ 2• Dependency-aware and compound vulnerability impact assessment
    ⤇ 3• Correlating classical CVSS with AI-specific threat vectors
    ⤇ 4• Reducing operational noise, unnecessary reboots, and security burnout
    ⤇ 5• Making high-quality vulnerability intelligence accessible beyond enterprise teams

    The core belief is simple: most security failures come from misjudged impact, not missed vulnerabilities. Accuracy, context, and accountability matter more than volume.

    I’m sharing this to invite feedback from folks working in CVE, OSV, vulnerability disclosure, AI security, infra, and systems research. Disagreement and critique are welcome. This problem affects everyone, and I don’t think incremental tooling alone will solve it.

    P.S.

    • Super appreciate everyone that's spent time reviewing my drafts and reading all my essays lol. I owe you 🫶🏻
    • ... and GoogleLM. These slides would have taken me forever to make otherwise.

    Take my CVE-data User Survey to allow me to tailor your needs into my design - lnkd.in/gcyvnZeE
    See more at - lnkd.in/gGWQfBW5
    lnkd.in/gE2wUqgc

    #VulnerabilityManagement #Risk #ThreatModeling #CVE #CyberSecurity #Infosec #VulnerabilityManagement #ThreatIntelligence #ApplicationSecurity #SecurityOperations #ZeroDay #RiskManagement #DevSecOps #CVE #CVEAnalysis #VulnerabilityDisclosure #SecurityData #CVSS #VulnerabilityAssessment #PatchManagement #AI #AIML #AISecurity #MachineLearning #AIThreats #AIinSecurity #SecureAI #OSS #Rust #ZeroTrust #Security

    linkedin.com/feed/update/urn:l

  5. Advancing AI by Accelerating Java on Parallel Architectures

    - The Java Platform is incorporating SIMD and SIMT execution models for faster computations.
    - These enhancements enable developers to build high-performance, data-driven applications.

    #Java #AI #ParallelProcessing #DataDrivenApplications #genai #aiml

    inside.java/2024/10/23/java-an

  6. 🐘 Unleash the power of LLMs on your own machine with Java! 🐘

    Dive into the world of Large Language Models and learn how to build a blazing-fast inference engine using pure Java, inspired by Andrej Karpathy. No need for cloud services or expensive GPUs!

    youtube.com/watch?v=zgAMxC7lzk

    #Java #llm #genai #aiml #graalvm #vectorapi #Devoxx

  7. 🐘 Unleash the power of LLMs on your own machine with Java! 🐘

    Dive into the world of Large Language Models and learn how to build a blazing-fast inference engine using pure Java, inspired by Andrej Karpathy. No need for cloud services or expensive GPUs!

    youtube.com/watch?v=zgAMxC7lzk

    #Java #llm #genai #aiml #graalvm #vectorapi #Devoxx

  8. 🐘 Unleash the power of LLMs on your own machine with Java! 🐘

    Dive into the world of Large Language Models and learn how to build a blazing-fast inference engine using pure Java, inspired by Andrej Karpathy. No need for cloud services or expensive GPUs!

    youtube.com/watch?v=zgAMxC7lzk

    #Java #llm #genai #aiml #graalvm #vectorapi #Devoxx

  9. 🐘 Unleash the power of LLMs on your own machine with Java! 🐘

    Dive into the world of Large Language Models and learn how to build a blazing-fast inference engine using pure Java, inspired by Andrej Karpathy. No need for cloud services or expensive GPUs!

    youtube.com/watch?v=zgAMxC7lzk

    #Java #llm #genai #aiml #graalvm #vectorapi #Devoxx

  10. 🐘 Unleash the power of LLMs on your own machine with Java! 🐘

    Dive into the world of Large Language Models and learn how to build a blazing-fast inference engine using pure Java, inspired by Andrej Karpathy. No need for cloud services or expensive GPUs!

    youtube.com/watch?v=zgAMxC7lzk

    #Java #llm #genai #aiml #graalvm #vectorapi #Devoxx

  11. If you’re having a hard time buying GPUs, one thing you can do to increase the performance of your AI/ML workloads is to let the CPU’s AMX instructions do some of that AI/ML work, lessening the need for expensive and hard-to-procure GPUs. earlruby.org/2023/08/accessing #aiml #ai #ml #amx #vsphere #gpu #gpus #xeon