Al Sargent

Business model innovation around Retrieval Augmented Generation from O'Reilly -- they have indexed all the content on Safari and are using it to provide answers grounded in vetted and credible content (their unique sauce). Another innovation here is to credit/compensate authors for the fraction of their work used in a generated answer. While this is progress, the more well-grounded the summaries look, the more dangerous the inevitable mistakes will be -- irrelevant documents will still lead to misleading summaries, and there will still be hallucinations because of interpolations with the text used to train Llama. At least based on the article, I don't see them employing self-checks or guardrails. I hope those are coming. https://lnkd.in/gqqHiR2D

42

1 Comment

Should every partner be a special snowflake? There's a delicate balance between building the meaningful relationships that make partnerships a unique GTM rhythm and building the operational efficiency to scale them. This is particularly difficult for partner enablement functions. Aaron Howerton and Adam Pasch and I got right into it on this episode of Literal Scratch. Also a little shout to Chris Lavoie, PhD... can't stop thinking about your post on leading indicators.

28

1 Comment

I see an industry wide need to include more functions and teams in the GTM motion, this one reflects pretty closely to what I have in mind https://lnkd.in/ek2iCWXb

11

🔍 Revolutionizing Software Testing with LLMs 🚀 Large Language Models (LLMs) are transforming the landscape of AI-driven testing. By integrating LLMs, companies can achieve higher efficiency, accuracy, and adaptability in their testing strategies, leading to more robust software solutions. 👉🏼 Enhanced Test Coverage: LLMs provide comprehensive analysis of complex codebases, ensuring no bug goes unnoticed. 👉🏼 Smart Automation: LLMs streamline repetitive tasks, optimizing testing workflows. 👉🏼 Predictive Insights: LLMs anticipate potential issues, allowing proactive resolution. 👉🏼 Adaptive Testing: LLMs continuously learn and adapt to evolving code patterns. 👉🏼 Intelligent Defect Detection: LLMs accelerate bug identification and fixing, reducing development cycles. Embrace LLMs to elevate your software testing to the next level! #AI #LLM #SoftwareTesting #Automation #TechInnovation

12

Anthropic's Claude 3.5: A New Benchmark Leader in AI In the rapidly evolving landscape of artificial intelligence, Anthropic's Claude 3.5 has emerged as a significant contender, surpassing OpenAI's GPT-4 in several key benchmarks. This latest model demonstrates superior performance across various tasks, highlighting the continuous advancements and competitive dynamics within the AI field. Claude 3.5 excels in natural language processing, exhibiting enhanced comprehension and generation capabilities. According to recent benchmarks, Claude 3.5 achieved a 10% higher accuracy rate in contextual understanding tasks and a 15% improvement in response generation compared to GPT-4. This achievement underscores Anthropic's commitment to pushing the boundaries of AI technology. The implications of Claude 3.5's success extend beyond mere competition. Its advanced capabilities promise practical applications across industries, from improving customer service chatbots to enhancing content creation and data analysis tools. For example, companies utilizing Claude 3.5 have reported a 20% increase in customer satisfaction due to more accurate and contextually relevant interactions. With AI rapidly becoming integral to various sectors, the emergence of superior models like Claude 3.5 marks a pivotal moment in the AI race. This progress not only benefits businesses and developers but also paves the way for more sophisticated and effective AI-driven solutions. hashtag#AIInnovation hashtag#Anthropic hashtag#Claude3.5 hashtag#BenchmarkLeader hashtag#ArtificialIntelligence hashtag#TechAdvancements

2

In my recent blog post on parsing complex PDFs using GPT, I explored the potential of incorporating confidence scores to quantify GPT’s accuracy in the results. By integrating confidence scores, we can establish a scalable and efficient document processing and data extraction workflow that requires minimal oversight and review, thereby optimizing automation and reliability. For this purpose, we will be using the log probabilities or logprobs. https://lnkd.in/gnHy_cz8 #llm #gpt #productivityhack #openai #logprob #ocr

4

Thanks to #genai360 for the shoutout here for Consilience AI and our AlphaIQ product. Davit Buniatyan Joseph Byrum, Ph.D., MBA

10

I shared a new Reforge artifact on Amplitude's PLG use cases 🔗 Use this template to: › Define your PLG use cases. › Evaluate them against 4 key factors (willingness-to-pay, motivation, ability, permission). › Outline the Growth Model Mix across acquisition, activation, and monetization. 👉 Bookmark it and share it with friends: https://lnkd.in/e9KB2EGz

36

2 Comments

🎯 Optimizing Marketing with Budgeted Multi-Armed Bandits 💡 Transform marketing strategies by treating scripts as multi-armed bandits (MAB), balancing exploration and exploitation for optimal results. 🧠 Introducing the new ω-UCB algorithm, which enhances campaign effectiveness by considering budget constraints and asymmetric confidence intervals. 💻 The article offers not only a theoretical discussion of the ω-UCB algorithm but also real-world demonstrations, complete with code and a summary video. 📈 Unlike traditional MAB models with fixed rewards and costs, this approach adapts strategies to variable call durations and expenses. 🚀 Boost campaign success further with customer segmentation, reliable reward proxies, and environmental factors.

1

1 Comment

The Forbes 2024 Cloud 100 List is live ☁ Congrats to all the honorees – the world's top 100 private cloud companies –including the 3 healthcare and life sciences companies featured this year: • Benchling - biotech R&D platform • Komodo Health - healthcare data analytics • Abridge - AI for clinical documentation For more on how AI is colliding with cloud computing, check out Bessemer Venture Partners's 2024 Cloud 100 report. Personally I'm focused on advancements in multi-modal AI, as applied to biomedical applications (Trend 3!): https://lnkd.in/euzurvQV

36

1 Comment

CRO and CMO Jessica Gilmartin shares a first-hand account of how Calendly revamped their lead routing, qualification, and GTM org. #plgplays #productledgrowth #revenueengine #valueengine #saas #saasgrowth #salesfunnel #buyersjourney #buyerenablement #gtm #saasbusiness #saasstartups #saasproduct #productmanagement #revops #leadconversion #businessgrowth #scalingup #revenuegrowth #revenuestrategy #gtmstrategy #revenueboost #monetization #revenuegeneration #productgrowth #customerengagement #customeracquisition #gtmmotion #gtmplays #customerjourney #plgstrategies #plg #slg #saleseffectiveness #bestpractices #expertadvice #customerrelationship #useracquisition #userengagement #useronboarding #customervaluecreation #productvalue #successstrategy #gtmomentum #gotomarket #valuecreation #bestpractices #customerfocus #customercentricity #saassales #saasmarketing #growthlevers #growthdrivers #leadmanagement #leadcapture #leadnurturing #leadrouting

10

For GenAI enthusiasts: How to Build AI Agents with LlamaIndex, MongoDB, and Claude 3.5 Sonnet. https://lnkd.in/gwcfbadD

9

My favorite quote from Aaron Allsbrook's webinar with SAS last week: "A true #digitaltwin needs to be hydrated with data. The connected digital twin is what we’re after. Something that is getting data to allow you to look at that operational asset, process, or industry and then put that POWER back into the end-user or operator view." 💥 I couldn't agree more! #IoT, #MachineData, and #DigitalTwins are best used when you can make sense of data to drive action.

9

Llama 3.1 is now available in Domino. Get started with one click and have the world’s most powerful #opensource #LLM at your fingertips. Learn: https://gag.gl/AZkJQS #AI #LLAMA3 #MachineLearning #GenerativeAI #Innovation

7

While IaC has integrated infrastructure into the app lifecycle, the increasing demand for cloud environments is turning it into a high-skill, high-stakes game—especially with AI workloads getting more complex. If we keep this up, we’ll need MIT-level talent just to meet basic cloud needs. Torque's GenAI capability really changes the game, crushing the complexity of Infrastructure as Code (IaC) freeing teams from manual configurations and letting them focus on what really matters. Finally, a tool that takes care of the heavy lifting so we don’t have to. #CloudAutomation #IaC #GenerativeAI #CloudManagement

4

GPT Pro Tip: generate clean tables for exporting to PDFs by adding "use markdown table format" to any prompt. Define any table columns or headers in the prompt. iDialogue #GenerativeAI for Salesforce

17

AI - so hot right now, but outside of trillion dollar valuations, competing models, regulations, and startup funding that dominates much of the discussion is the foundation for which all of AI relies on, data. Kaladhar Voruganti and I have started a series to walk you through the most important piece of the AI puzzle.

15

AgTech Ecosystem - the Acquired Podcast has a lot of learnings for startup operators. It focuses on telling the stories of significant acquisitions and companies. There are great episodes on Microsoft, NFL, and NVIDIA. Each episode they focus on a few key themes: (1) both co-hosts grade the acquisition from the acquiring company's point of view; (2) how did the numbers and/or strategy play out - how much did the acquisition contribute to revenue/margin and strategic direction; (3) what would have happened if the deal had not happened; and (4) what type of acquisition was it - product, team, or business line being the most common selections. Co-hosts Ben and David do a great job of delivering the background fact pattern, adding the flavor of the activities that led to the acquisition, and then going through the factors above. I find the podcasts to be very informative and entertaining (maybe because I've been a tech fanboy for about 40 years :) and decided to go back to listen all the way from the beginning (2015). There are several items of interest from the first 21 episodes: 1) The first few episodes really are the Hall of Fame (Mount Rushmore) of pre-2015 tech and entertainment M&A. Episodes on Disney-Pixar, Facebook-Instagram (so far the gold standard), Amazon-Twitch, Sony-Bungie, Apple-Siri, Google-YouTube, and eBay-PayPal are all reviewed, as well as the non-acquisition of Facebook-Snapchat. You get a drive down memory lane for each of these through a 2015 lens and you great insight into how the acquiring companies thought about the acquisition and evaluated the results post-acquisition. 2) One of the best parts for startups is the mindset of the acquiring company. Ben and David have operator and investor experience and are just really plugged in geeks who like this stuff - it's obvious from the podcasts how much they enjoy and care about getting the stories and the details right. This includes really deconstructing the investment thesis and how it actually played out. 3) This is so important for startups in AgTech - remember that IPOs are getting tougher (BG2 podcast thinks you need a clear path to $1B in 5 years with 20-30% YoY growth rates - well good luck on those metrics in AgTech) so M&A is the most likely path forward. Given that, startups really need to focus on where they can create 1+1=3 value like Instagram and PayPal were able to do with Facebook and eBay. Figure out what the potential acquirer is focused on and how your startup can help them get their faster - sometimes as simple as an acqu-hire and sometimes a strategic combination of products and partners to accelerate revenue growth in a key category. (Continued in first comment ...) Rhishi P. Sachi Desai Carter Williams Rob Trice https://lnkd.in/gb48duzf

34

13 Comments