Robert Brooks IV

Exciting news! Narratize, one of the portfolio companies in HWI Fund II, has been accepted into the NVIDIA Inception accelerator! Congratulations to Katie Trauth Taylor, PhD, and the team! Check out the details in their latest blog post. #GenerativeAI #AIinvesting #womenentrepreneurship #howwomeninvest Read more here: https://lnkd.in/g9tJaaHE

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Stop Talking. Start Doing. Everyone has ideas, but it's turning them into something tangible that counts. Let's get down to business and unlock the value in your data. I'm pumped to help leaders like you with real-world strategies and tools to use data like a pro at InnoLead's "Leveraging: AI to Creating Real Business Value" event in Sunnyvale, CA, on May 16th. #stoptalkingstartdoing #innovation #technology

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We recently announced our newest product updates at LILT AI Day. The highlights: * AI Review -- automated quality scoring based on custom MQM templates. * V3.5 Models -- 100x performance / cost improvement relative to GPT 4. * No code workflow builder -- orchestrate models, data, and people without having to write code. Link in the comments below! #ai #GenerativeAI #EnterpriseAI #Localization #Globalization #l10n #i18n

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We've all heard of FOMO, but what about FOFU? 🤔 FOFU = fear of f***ing up 😨 And FOFU is higher than ever today. Manny Medina, CEO at Outreach, brought this up during his opening keynote at #RevOpsAF 2024 in San Diego a few weeks back. He calls it the no-decision epidemic. Because buyers are looking at opportunities, and choosing to "sit this one out." Because no one is getting fired for NOT making a decision, for continuing with the status quo. Because in today's market, FOFU > FOMO. So how do you flip this around? Manny offers up a few options, but my favorite is 👇 Micro-commitments 🤏 Instead of focusing on the macro-commitment of the deal, Focus on those micro-commitments to things like: Time 🕰️ Change 🤨 Investment💰 Make it easy for your buyer to take that first step, and then implement those micro-commitments at scale. Do this, and you'll be on your way to making sure that FOMO > FOFU, and not the other way around. #revops #revenueoperations #salesops #salesoperations #marketingops #marketingoperations #mops #sops #gtmops #alltheops

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PolyAI just announced its Series C fundraising with participation from Hedosophia, NVIDIA, Khosla Ventures. I've spent the last 5 years in the voice AI space, the last 18 months at PolyAI, and there is a reason PolyAI is the leading technology worldwide. The passion of PolyAI's people, the innovators who are ready and enabled to bring this technology to their businesses, and the end-users who are tickled pink by their interactions with our voice assistants in 15 languages and counting. This is just the beginning for us. The early adopters have deployed our technology and now the rest of the innovators will follow. If you are ready for meaningful change to your cx, look no further, you've found the best technology on the planet. #polyai #fundraising #fundraise #nvidia #khosla #innovation #genai #generativeai #voiceai #voiceassistants #pressrelease #news #fundraisingnews #cx #airevolution #customerservice #contactcenter #callcenter

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My paper on the Cruise robotaxi pedestrian dragging mishap has been updated and is now available in its final form. I'll be presenting this paper at Safecomp in September, but you can see the preprint right now. Thanks to the SafeComp reviewers for their review comments! If you haven't had a chance to look at this paper before, the short takeaway is that there is a lot buried in the external reports that is not obvious from a casual reading. My paper is the result of carefully assembling the pieces to tell a more direct story of the events that unfolded. Title: Anatomy of a Robotaxi Crash: Lessons from the Cruise Pedestrian Dragging Mishap (Safecomp 2024 practical experience report) Abstract: An October 2023 crash between a GM Cruise robotaxi and a pedestrian in San Francisco resulted not only in a severe injury, but also dramatic upheaval at that company that will likely have lasting effects throughout the industry. Is-sues stem not just from the loss events themselves, but also from how Cruise mishandled dealing with their robotaxi dragging a pedestrian under the vehicle after the initial post-crash stop. External investigation reports provide raw material describing the incident and critique the company's response from a regulatory point of view, but exclude safety engineering recommendations from scope. We highlight specific facts and relationships among events by tying together different pieces of the external report material. We then explore safety lessons that might be learned related to: recognizing and responding to nearby mishaps, building an accurate world model of a post-collision scenario, the in-adequacy of a so-called "minimal risk condition" strategy in complex situations, poor organizational discipline in responding to a mishap, overly aggressive post-collision automation choices that made a bad situation worse, and a reluctance to admit to a mishap causing much worse organizational harm down-stream. https://lnkd.in/e5h84-up

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NVIDIA CEO says – “You DON’T need to learn coding” - because by 2025, 70% of new apps will use no-code or low-code tech. This is a stark difference from 2020, when only 25% apps were developed through low-code systems. The benefits of Low-Code No-Code (LCNC) are simple but super effective: It is nearly 10x faster, reduces tech gap, and provides high levels of flexibility and automation. 🈸28% users mastered app development in <2 weeks. 🈸84% organizations leverage low-code to free up IT resources. 🈸80% users report automation of routine tasks, saving valuable time. Wondering what tailor-made solutions LCNC can help you build? - Sales CRM - IT Systems Helpdesk - Internal process automation - Complaints Handling system - Project Management system - Inventory Management system - Workforce Management system - Maintenance management system And so much more! Get Started on your No-code low-code journey today with AppSavy Custom Application Development Platform. #technology #nocode #coding #career #future

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Solitary LLMs are impressive, but several can work together as a Multi-Agent System to astounding effect and overcome solo LLM (GPT-4o, Claude 3, Gemini) limitations. Hear all about it in today's "Five-Minute Friday" episode. In a bit more detail: • In recent weeks, OpenAI's GPT-4o and Google's Project Astra showcased A.I. agents that engage in humanlike conversations and analyze real-time video. • Despite such impressive capabilities, single A.I. agents still struggle with many categories of complex tasks. • Thoughtfully linking individual LLMs together into a Multi-Agent System (MAS) enables them to work together, assign tasks, build upon each other's work, and deliberate to find solutions, in aggregate exceeding the capabilities of a single LLM on its own... often without any decrease in compute efficiency. • As an example, a DARPA experiment demonstrated 3 agents (named Alpha, Bravo, Charlie) collaborating to defuse (virtual!) bombs efficiently. • In an Massachusetts Institute of Technology study, two chatbots solving math problems outperformed a single agent through dialogue and updating each other's answers. • Microsoft developed a software-writing MAS with specialized roles (Commander, Writer and Safeguard; see the image for this post) wrote code 3x faster without sacrificing accuracy. • As always, there are potential risks, e.g.: illogical solutions cascading through the team, agents getting stuck in loops, and malicious exploitation. • Commercial interest in MAS is accelerating, with frameworks like AutoGen and Camel making it straightforward for you to get started with MAS today yourself. What in your industry could be automated or improved by MAS where single-LLM approaches aren’t sufficiently effective? 🤔 For more detail on all of the above, check out today's episode (#788)! The Super Data Science Podcast is available on all major podcasting platforms and a video version is on YouTube. #superdatascience #machinelearning #ai #llms #multiagentsystems

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Trying to leverage xLMs through prompt-tuning, fine-tuning, or RAG? This one is for you.

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CS Leaders based out of the SF Bay Area: Join us in Menlo Park next Friday (6/13) for our inaugural "Application of AI in CS" monthly luncheon. Our featured guest, Ashvin Vaidyanathan (VP of Customer Success and Insights at LinkedIn), will kick us off with how the LinkedIn CS team is embracing AI to increase customer value and efficiency. We will follow that with a roundtable discussion on how AI can help with your current priorities, how are you leveraging AI today, are there any adoption hurdles that you are running in to? https://lu.ma/g9u8mu8q

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THIS... is why we started Summit Venture Studio... These are 27 software development projects Spencer Walker and I worked on while inside the University of Utah. The Y-axis is Millions of dollars (valuation). The X-axis are value inflection points. The two companies that had the highest value at exit/raise in this chart were actually valued much higher but it skewed the graph so I am just showing how much they raised. The GREEN all exited or raised money, the BLUE were all licensed to established companies so a real value was never set after that and the RED were shut down. An interesting point to think about is that these projects were "assigned to us" and were not "chosen" as good business opportunities. Now we are screening the deals we work on for commercial viability. I am super excited for the future. Who wants to come and play with us and start a company with us? We have 8 in the pipeline and I just finished a meeting where we agreed to launch our next company hopefully in the next few weeks.

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Geography is destiny

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As we look ahead to 2025, it's becoming clear that the future of enterprise AI lies in compound systems, not monolithic models. Compound AI systems combine multiple models that work together iteratively, coordinating and leveraging external tools to evaluate, refine, and improve their own results. 🔄 The benefits are clear: ☑ Better performance than individual models ☑ Faster and less expensive iteration  ☑ Granular access controls on sensitive data  ☑ More reliably ensure that models behave as intended ☑ Flexible performance-cost optimization Early examples like AlphaCode 2, LLM Debate, and CoT-SC are already showing impressive results. 📈 As we move towards 2025, compound AI systems will become increasingly critical for enterprises looking to deploy AI at scale reliably, securely, and cost-effectively. 🎯 Check out my latest B2BaCEO newsletter for a detailed look at where AI is headed and what it means for founders: https://lnkd.in/gRrzX9nq h/t to Berkeley Artificial Intelligence Research and my colleagues Jaya G. Andrew Han Courtney Fiske for their research help

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The infrastructure team at Orb thinks a lot about our production oncall rotation, and how to scale and shape it over time. Here are some core operating principles we've landed on that work well for us so far (of course, any such list will be stage dependent, so take in a high-sodium way): 1/ Try to keep most engineers on-call, avoiding the outcome where a small fraction bear the brunt of instability. This helps build a shared mental model of pain points — calibration on issues is important. 2/ Remove all judgement calls possible at 3am; this requires clear playbooks, links to dashboards as entrypoints for investigation, and alignment on when to escalate (oh -- and train people to bias towards escalation; the natural tendency, especially for newer folks, is to avoid it). 3/ At each weekly handoff, explicitly document what's gotten better and what deserves investment. We also rate each shift (using Asana status updates) between 'on track', 'at risk' to 'off track'. The update should reach the whole engineering team, if not the whole company. 4/ We've gotten a lot of mileage out of a separate #oncall channel with a single thread per investigation. We still try to minimize noise in the alerts/pages channel, but this new venue has become an easier place to rope folks in and ask for help. This channel is also something non-engineers can reasonable track. 5/ As an infra (and in other orgs, SRE, platform, etc.) team, you have to dedicate real roadmap time to investing in oncall improvements in addition to each individual oncall doing so. Some projects just don't get done incrementally. We've done a ton of this — from better instrumentation to observability (whether its metrics or database transactions) to ergonomics (where do alerts go, how do they get deduped, etc.).

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C++ is utilized across many software libraries for speed, and is widely used in operating systems, financial applications, and scientific simulations. Production ready generative artificial intelligence applications continue to implement C++ to ensure application performance, reliability, and flexibility. Open source LLaMA.cpp, GPT4All, Libtorch, and TensorFlow C++ permit a broad range of fast machine learning implementations. TensorRT (nVIDIA) and OpenVINO (Intel) heavily rely on C++ software designed for hardware specific to the manufacturer. Discussion: https://lnkd.in/g25VDu6E #cpp

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Technical report: Learn about fine tuning  Small cheaper to run models can do better than GPT-4 with a small amount of fine-tuning. "We find that 4-bit LoRA fine-tuned models outperform base models by 34 points and GPT-4 by 10 points on average" How to fine-tune? LoRa method is the most well known and can be done on any decent gaming PC for learning. Many YouTube tutorials can be found. Having your own fine-tunes gives your business something unique in the market, you build your dataset up over time, building that value. Paper: https://lnkd.in/gi6PqyYt

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If you're in Seattle for Microsoft Build this week, stop by the Expert Meetup Space (FP44) and chat with us about GraphRAG! Learn how to extract a knowledge graph from your content, using LLMs, and enrich entities with Wikipedia. Use the KG to provide greater context to your RAG pipeline, with GraphRAG. Blog: https://lnkd.in/gE3-DqNS Code: https://lnkd.in/gw2GWhCC Demo: https://lnkd.in/gniGn_3z #microsoftbuild #unstructureddata #knowledgegraph #graphrag

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Zoom has been using the power of LLMs to enable novel platform features like AI Companion. Excited to see that #DBRX will enable enterprises like Zoom to cost-effectively build, train, and serve their own custom LLMs! Learn more about DBRX here👇

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