Ashutosh Dhodapkar

During yesterday's LibreQoS APNIC webinar, I posed the question: won't more bandwidth solve these problems? As Herbert Wolverson said, yes, more bandwidth is good, but, still these problems remain if queueing is done incorrectly. Here's my take on why bandwidth alone is not as good as bandwidth + good queueing policies: Generally it was believed that 'data is important, so don't throw it away; hang on to it and send it later'. In practice, this has proven to be suboptimal as two issues may emerge: 1) latency increases for some flows due to heavy demand from other flows using the same bottleneck link, 2) even a single flow can have excessive latency due to aspects of typical TCP behavior (referred to bufferbloat) when the buffers grew large enough that the data being buffered was retransmitted anyway. It turns out that not all data is equally important. Active Queue Management is the art of deciding priorities, both in deciding what data to throw away, but also in allowing some later arriving data to be transmitted ahead of data in another connection that arrived before it. These problems have been studied, and good solutions have been found by using certain queueing policies in routers and switches, referred to as “fq_codel’ and “cake”. These track the different flows not by classifying the data, but by watching the behavior. Flows that send relatively little data (DNS lookups), or at a measured pace (video chat) have priority over flows that send a lot of data as quickly as possible (App and System updates, Video and ISO downloads).

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If you're looking for inspiration and advice on how to grow your business from its early stages to scaling it at incredible rates, have a listen below. The Hiveway Inc. founders sit down with CanadianSME Small Business Magazine to discuss the highs and lows, and perseverance required - to take an idea to becoming a leader in a global partner ecosystem.

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Let's finally get rid off the "VC alphabet song" and redo the system to become more founder friendly. "The benchmarks set by funding stages are often arbitrary and not necessarily aligned with the actual development needs of individual startups." #vc #venturecapital #founder #fundraising #startups #fundingstages #funding #fundingrounds #pitchbook

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Excerpt from an Angel Squad memo that we invested in recently: “[Company] is led by a team of scientists and engineers with PhD-level expertise in Machine Learning, Engineering Simulations, and Computational Materials Science. The team is headed by CEO, [Name], who previously led AI development at two early-stage startups. [Name] is joined by CTO, [Name], who has deep experience in machine learning and materials science, and Chief Science Officer, [Name], a doctoral researcher at the [School]. “ Investing at the earliest stages of value creation often means taking big bets on a founding team. At Angel Squad and Hustle Fund, we love founders with deep expertise and super domain knowledge, particularly in deep tech verticals.

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I like this idea of "technical taste". It gets into where software engineering is as much creative art as it is science. Four great takeaways (IMHO) for software devs in this era in particular: 1. Aspiring engineers should cultivate a sense of curiosity, experiment with different tools and technologies, and embrace a mindset of continuous learning. 2. AI has the potential to streamline processes and enhance productivity for engineers, but it may also lead to disruptions in traditional software development workflows. 3. Developing technical taste and judgment is essential for making informed decisions about which technologies and approaches to pursue. 4. Collaboration and open-mindedness are key to leveraging the full potential of AI and staying ahead of technological advancements. I also really liked these two quotes from Sam Schillace: 1. "The right time to do something is when you have that feeling in the pit of your stomach that's like, 'oh, this is a great idea and it's going to suck to build because nothing's ready yet.'" 2. "Technical taste is like, 'how well have you consolidated that set of experiences and heuristics into judgment that you can apply accurately when you see new things?'" 3. "It may be the case that very small teams can do very large projects, or like we were talking about before, it may be the case we're just going to get really ambitious about what we try to do with the same size of teams, which is kind of where I would put my money." Great job on continuing to put out great episodes, Brett Berson and team First Round Capital! #ai #engineering #softwaredevelopment

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🌏 𝗠𝗲𝘁𝗮'𝘀 𝗠𝗮𝗿𝗸𝗲𝘁 𝗠𝗼𝘃𝗲𝘀 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗘𝘃𝗼𝗹𝘃𝗶𝗻𝗴 𝗔𝗜 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲 🌎 As a staunch supporter and investor in Meta, it’s disheartening to witness a 16% plunge in its stock despite the company surpassing first-quarter expectations. This stark drop, primarily driven by weaker-than-anticipated revenue guidance for the upcoming quarters, underscores the volatility and challenges within the tech sector. What’s particularly interesting—and concerning for some investors—is Meta's substantial investment in hardware through partnerships with companies like NVIDIA, which was pointed out by Chamath Palihapitiya in a recent discussion on the All-In Podcast. Meta may be overspending on NVIDIA's capabilities, which are traditionally strong in training but less so in inference, a critical component of AI efficiency and cost-effectiveness. This misallocation might not be fully appreciated by the market, contributing to the sharp decline in Meta's stock. Aligning with Chamath's critique, Andrew Ng's recent speech at Sequoia Capital emphasizes the growing importance of inference over training in AI development. He argues that the future of AI lies not just in processing vast datasets but in making smarter, iterative improvements through 'agentic workflows.' This approach mimics human-like reasoning and problem-solving, significantly enhancing AI's applicability and effectiveness across various sectors. The juxtaposition of Meta's current strategy with Andrew NG's vision presents a fascinating discourse on the strategic decisions tech giants must make. As investors and industry observers, it's crucial to assess not only the financial metrics but also the technological and strategic underpinnings of these companies. Are they investing in the right technologies for the future, or are they anchored to the past? This scenario serves as a critical lesson for venture capitalists and tech entrepreneurs alike. As we navigate the complexities of AI investments, understanding the distinction between mere computational power (training) and actionable intelligence (inference) will be key to identifying and leveraging the next wave of innovations in technology. Here are all my sources for the ones interested: Meta Earning release reviewed by CNBC: https://lnkd.in/ddGia5kK All-in Podcast clip on Chamath point of view on Meta: https://lnkd.in/dfs7JQG4 Andrew NG at Sequoia: https://lnkd.in/dqnvex2u #AI #VentureCapital #Meta #TechnologyTrends #Innovation #ArtificialIntelligence #NVIDIA #Groq #InvestmentStrategy

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I'm really intrigued by this idea (not mine) that some bitcoin mining companies (Iris, Cleanspark, etc) have successfully built low-cost power shells that can now be leveraged by AI compute needs -- where power itself is becoming the gating factor in the continuing growth of AI. I think this will become a real 2025 story -- as the gating factor of "chip shortage" lessens, and the gating factor of "cheap power" rises in significance. There's not really a venture capital angle here, but there is a public market one. Perhaps more importantly, it becomes a touchpoint between "crypto" and AI. Something to ponder and keep an eye on (full disc: I own a bunch of bitcoin miner stocks, including those mentioned above).

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Generative AI is definitely in a hype cycle but has that hype translated into real-world consequences? According to a recent Harvard Business School report the answer is a resounding yes. The HBS report indicates that the demand for freelancers in writing and coding has plummeted by 21% since ChatGPT's launch in November 2022. To put this into perspective, a drop of over 20% in a stock index is considered a full-blown stock market crash. This is no minor correction for the digital freelancer market. ChatGPT and other AI technologies are already having transformative effects across industries and the technology will only continue to improve. My bet is that current AI is at least as transformative as the rise of email (which had massive impacts on the corporate landscape) with the potential for even greater effects. What are your thoughts on the impact of AI? How is it affecting your industry?

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With the Synapse story still unfolding, it felt like an apt time to revisit the topic of BaaS and sponsor banking so I spent the weekend getting smarter ... 🚨 I covered some of this in a prior post, but wanted to dive a little deeper and spend time discussing: 🔵 The role that BaaS providers and Sponsor Banks play 🔵 The implications of the Synapse bankruptcy proceeding 🔵 Where I think the market goes from here 🔵 Who I think the winners will be longer term (e.g. infinant Inc + Coastal Community Bank) 🅣🅛🅓🅡: I'm hopeful that this is a wake up call to regulators to modernize the process and requirements associated with obtaining a bank charter. In an ideal world, all fintechs that touch the movement of money should have a clear path to earning a charter; thus ensuring that those same fintechs are held to the same regulatory standards that banks are held to. Read more here 👉 https://lnkd.in/e9FmKNM5 And as always, please share your thoughts or comments below 🗣 Some of these points can be polarizing - but all conjecture is welcome and encouraged - the most effective way forward is one that incorporates diverse perspectives! h/t: Jason Mikula for the great coverage of the unfolding events! cc: BankTech Ventures #BaaS #communitybanking #innovation

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Connie Kwan 🎤 Story-led Leadership, Chief Product Officer at Nobody Studios, is joining Sejal Thakkar and I on tomorrow's Making of a Nobody podcast. Join us live at 10:00 am PST as we share how to take an idea to an early stage-product. Link is in the comments, see you there! #product #startup #tech #futureisnow #venturestudio

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Y Combinator（YC）のRequest for Startupsについてまとめた記事の第2弾をnoteに投稿しました。「AIツール」、「防衛・宇宙」、「製造技術」、「気候変動」、「AR/VRの実用」、「金融」の6つのグループに分類し、それぞれ現状の課題およびYCの興味についてまとめましたので、ぜひご覧ください。引き続き、気になる分野については、現在の競合状況や不十分な技術等について深掘りをしていく予定です。 第2弾のブログ記事はこちら（Here is the blog post for the second part:）↓ https://lnkd.in/gvrEqqfH 「ヘルスケア」、「企業向けソフトウェア」、「AI／機械学習の実用化」のグループについてまとめた第1弾はこちら（The first part, which covers "Healthcare," "Enterprise Software," and "Practical Applications of AI/Machine Learning," can be found here）↓ https://lnkd.in/gMicj2Jp *Although the articles are in Japanese, please feel free to contact me in English if you are interested in the content. I have posted the second part of my article series on Y Combinator’s Request for Startups on note. In this installment, I have categorized the topics into six groups: "AI Tools," "Defense & Space," "Manufacturing Technologies," "Climate Change," "Practical Applications of AR/VR," and "Finance." Each group includes an overview of current challenges and YC’s areas of interest. Please take a look. I plan to continue delving into areas of interest, including the current competitive landscape and insufficient technologies.

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Reflecting on the future of artificial intelligence, it's clear that the next decade will be transformative. San Francisco is already buzzing with conversations about compute clusters escalating from billions to trillions of dollars. This scramble for power contracts and resources underscores an impending industrial mobilisation unlike anything seen in recent times. By the end of the decade, the US will see significant growth in electricity production, driven by the demands of AI. The AGI race is truly on. Predictions suggest that by 2025/26, AI will surpass the cognitive abilities of many college graduates, leading us towards superintelligence by the decade's end. This rapid advancement will not only revolutionise technology but also trigger intense national security responses, possibly leading to unprecedented global competition. Despite the current hype, many still underestimate the impact of AI, viewing it as merely advanced word prediction. However, those in the know—primarily based in San Francisco's AI labs—understand the profound changes ahead. These experts, once considered fringe, are now seen as visionaries, drawing parallels to historical figures like Szilard and Oppenheimer. In the coming years, the world will awaken to the reality of AI's capabilities. Those of us who see this future now are preparing for a wild ride. #AI #AGI #FutureTech #Superintelligence

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Starting a new fun project with Victor Lee - an AMA series with early stage founders. There are many podcast shows featuring successful, famous entrepreneurs. But what about those who are still relatively early in their journey, perhaps just one step ahead? The zero-to-one founders who have recently cracked the product-market fit and raised Seed or Series A capital. They may not have figured out everything yet, but they have fresh, relatable tips and advice to share. We’ll invite early-stage founders for a one-hour AMA session. Afterwards, we’ll create a public webpage featuring each Q&A session with media clips and transcriptions. This will be 100% free and open to the public. Our first AMA (June 11 1pm PST) will feature Will Drewery, whose company (Diagon) recently raised $5.1 million in Seed funding. We’ll get to know Will better and cover topics such as tips on raising funding in this tough environment. It will be a fun AMA, and you can register for free using the link below. RSVP now!

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There are two interesting and relatively new/emerging revenue models in hardware space. (1) Software Enabled Hardware Hardware is sold at lower but slowly improving gross margins (eg 20-40%), and software recurring revenues layered on top. Software sells at higher margins, enabling blended margins to appear in 50%+ category. These are applied in situations where hardware is not expected to be replaced or greatly improved upon in deployment for a significant number of years to come. Consider your car, or military equipment, or even infrastructure equipment. As always, there are often multiple business/revenue models utilized by different players in the same industry. (2) Hardware As A Service Hardware and software are bundled and sold with annually recurring revenues. Often multi-year contracts are signed to be able to amortize hardware over time, and enable blended gross margins over the length of the contract to be high (approaching 60-75%). This is more common in situations where vendor takes responsibility to upgrade hardware as needed along the way to provide maximum and highest functionality to the customer. Hardware inventory costs are, over time, passed on to suppliers or third party financing parties in lieu of few gross margin points. Consider robots as a service in factories (ala Formic), or AI-enabled equipment (eg Evolv, Lumafield etc). Hardware innovation will require deeper investigation, experimentation, and understanding of business/revenue models to fit customer needs as well as to maximize value for the innovating company. Strong and experienced management teams work hard to minimize sales friction, inventory costs etc, but also maximize gross margins, customer stickiness, and ability to upsell during the life of a contract.

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Boom’s rent reporting infrastructure is truly scaling. This is what API-level performance and pricing looks like. We are scaling our product with tech, rather than headcount. We do monthly retrospectives on our data verification and furnishment performance, and this month we stretched it back to compare against the prior year. The important metric we focus on is: # of new conversations initiated each month per active tradeline (i.e. subscribed Boom renter). 📉 In the past year, we’ve reduced this number by 95% (!!) The formula here is # of new conversations divided by # of active tradelines… let’s chat about these two variables first: 1. Active Tradelines 💥 In this same time period, we grew this number by 670% (!) 2. Customer Conversation Volume 🎧 In this same time period, we reduced this number 64% The first variable is easy to attribute—we’re rapidly scaling and word about BoomReport is starting to get out. The second variable—Customer Conversation Volume—is more complex. Even with our customer base scaling, how are we driving down Customer Conversation Volume? There are two initiatives we’ve been focusing on: 1. Technology ⚙️ We are continuously making updates to our product to ensure we are delivering an optimal user experience, and direct customer feedback drives a lot of our new feature releases. Here’s a timeline and description of some of the contributing releases: ➡️ Apr23: Payment Verification Service feature to increase accuracy and speed ➡️ May23: Tradelines Management feature, including furnishment error management ➡️ Jun23: Tradeline Timeline feature; automated tradeline syncing for TU, EXP ➡️ Jul23: Direct PMS integration ➡️ Aug23: Seamless Moving Experience feature to allow renters to transition between units without disrupting their subscription ➡️ Sep23: Credit card linking via Plaid, Partner-enrolled user access to app ➡️ Oct23: Boom Global Subscription to enable more seamless billing experiences; direct PMS integration ➡️ Jan24: PMS ‘click-to-sync’ integration to improve data latency ➡️ Apr24: Furnishment Audit Dashboard updates (v2) 2. People & Processes 🤝 Meanwhile, our customer service team has made great strides to level up customer support and surrounding workflows. For instance, in the past year, our response time has dropped from >8 minutes to ~1 minute (excluding chatbot responses). Some contributing upgrades include: ✅ Improved trainings for support team members ✅ New escalation pathways ✅ New workflows in our chatbot (updated issue trees to help renters self solve and help agents resolve issues quicker) Product updates and customer support improvements have been powerful initiatives to help us build a true rent reporting infrastructure for PMSs and landlords. And looking beyond this, we have numerous other levers we haven’t pulled yet, so we think we can drive even more order-of-magnitude improvements. Interested in learning more? DM me and let’s chat 💥 #RentReporting #CustomerSupport #SaaS

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Introducing the Alinia AI Alignment Platform. From their announcement: "Alinia AI enables companies to evaluate the performance of their GenAI applications and obtain evidence on how aligned these are to their values, policies, and business preferences. Following the performance assessment, Alinia AI recommends the best next actions to further guide and control LLM output and improve alignment."

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Days after celebrating Ibotta’s IPO, Hans Tung shares his thoughts with TechCrunch’s Mary Ann Azevedo on down rounds, AI, and more: 📈 On down rounds: “It’s like getting a report card or test/exam score. It doesn’t really matter until you have an exit. An #IPO is actually just a milestone, not the end game. An IPO is the beginning of public investors being along for the ride. So when you think in longer-term valuations, up or down temporarily doesn’t matter as much as generating a big outcome at the end.” 🤖 On #AI: “You can argue that we’re only in the first half of the first inning for AI… You do see a lot of crazy rounds happening at the beginning of a boom, but there will be bifurcation. There will be companies that end up doing great, and most companies may not. You’ve gotta still be very thoughtful about choosing which ones have a chance of being around for a very long period of time." 💡On our new name: “We picked the name Notable because we want to put the focus on the founders. We invest in notable founders, notable causes, notable ideas—even notable investors."

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As someone who follows the world of AI closely, I was excited to read about Sandeep Nailwal's new venture, Sentient. They just raised a whopping $85 million to build an open-source, decentralized AI platform. That's a big deal! 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝗰𝗮𝘂𝗴𝗵𝘁 𝗺𝘆 𝗲𝘆𝗲: 𝗢𝗽𝗲𝗻𝗻𝗲𝘀𝘀 𝗮𝗻𝗱 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆:Sentient is built on blockchain, which means everything is open and verifiable. No more shady algorithms! This is a big contrast to closed-source projects like some from Google and Meta. 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗣𝗼𝘄𝗲𝗿:Sentient is all about the community. Developers will be rewarded for their contributions, which is a major shift from the current model where big companies reap all the benefits. 𝗙𝗮𝗶𝗿𝗻𝗲𝘀𝘀 𝗳𝗼𝗿 𝗔𝗹𝗹:Nailwal believes AI development shouldn't be controlled by a few giants. Sentient aims to level the playing field and create an "AI economy for all." 𝗡𝗼𝘄, 𝘀𝗼𝗺𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗿𝗲𝗺𝗮𝗶𝗻: 𝗖𝗮𝗻 𝘁𝗵𝗲𝘆 𝗰𝗼𝗺𝗽𝗲𝘁𝗲 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗯𝗶𝗴 𝗴𝘂𝘆𝘀?OpenAI, Google AI—these are established players with massive resources. Can a startup like Sentient truly 𝗜𝘀 𝗮 𝘁𝗼𝗸𝗲𝗻 𝗰𝗼𝗺𝗶𝗻𝗴? They haven't announced a token yet, but it sounds like they might in the future. This could be a game-changer for incentivizing the community. Overall, Sentient is a breath of fresh air in the AI space. Their focus on openness, fairness and community engagement is exciting. While they have a tough road ahead, I am definitely keeping an eye on their progress. This could be the start of something big! 𝗪𝗵𝗮𝘁 𝗱𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝗦𝗲𝗻𝘁𝗶𝗲𝗻𝘁? 𝗟𝗲𝘁'𝘀 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀! https://lnkd.in/d_U5syCi #ArtificialIntelligence #AI #MachineLearning #FutureofAI #AIRevolution #OpenAI #DecentralizedAI #BlockchainAI #CommunityDrivenAI #FairAI

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