Sandeep Bhadra

ISP Strategic Leadership, Engineering, and Operations As an organization scales, there is often a need to separate strategic technology leadership under the CTO from internal execution under engineering and operations management. This allows the CTO to focus on outward-facing duties while enabling streamlined operational efficiency. However, it's crucial to recognize the differing motivations and needs of these distinct technical roles. On one hand, engineers thrive on tackling interesting, challenging projects that push their abilities and knowledge. They value working alongside capable peers, genuine recognition of technical accomplishments, and contributing to products/services that reach the market. In contrast, operations teams should strive for repeatable processes, continual improvement, and driving efficiency at scale. Their priorities revolve around standardizing workflows, minimizing disruptions, and incrementally optimizing existing systems and procedures to maintain consistent service delivery as the company grows. An effective organizational structure acknowledges this dichotomy, fostering an environment that fuels engineering innovation while providing operations with the stability and process-orientation they require. Striking this balance enables the company to stay agile and innovative through its engineering efforts, while simultaneously scaling operational execution in a reliable and repeatable manner. Competitive compensation remains an important motivator across both domains. By properly aligning structural elements, motivational factors, and leadership priorities, a rapidly growing ISP can position itself to attract and retain top talent across engineering and operations, driving sustainable growth and success in the dynamic technology landscape.

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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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This is quite a piece on accusations of unethical pay-to-play within the #cyber #VC ecosystem. -Guaranteed first-year sales for portfolio companies -Formal loyalty program for CISOs -Points awarded within the program for CISO commitment level to portfolio companies (meetings, PoCs, product purchases) -Share of GP fees for CISOs in the loyalty program https://lnkd.in/gDta7Gp7

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Open-source models can be a strong lever for increasing gross margins at AI companies, especially those that have hefty cost structures (e.g., enterprise sales orgs that require significant customer success or implementation resources, as well forward-deployed AI services models common in healthcare and life sciences). One of many reasons to maintain a modular and flexible stack with minimal dependencies when building an AI company. More on the importance of flexibility in the AI stack: https://lnkd.in/eA2XATRk h/t Delip Rao #ai #artificialintelligence #generativeai #healthcare

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I had a lot of fun recording a podcast episode with Shiva Singh Sangwan. We discussed the evolution of Humba Ventures & Susa Ventures; tips for raising and building a fund; how to improve investment sourcing & picking; the role of luck in investing, and so on. https://lnkd.in/eiqsStej

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#ObsessivelyEnthusiasticInvestor #UnreasonablyEnthusiasticInvestor #IrrationallyEnthusiasticInvestor at REFASHIOND Ventures: The Industrial Transformation Fund. We look for the people we believe are doing the best work in Industrial Transformation & Supply Chain Technology; Attempting the impossible. Then we go all-in on them. With obsessive and unreasonable enthusiasm. Join us. #IndustrialTransformation #SupplyChain #Innovation #Technology #Startups #VentureCapital #DemandTheImpossible #UnreasonableEnthusiasm #ObsessiveEnthusiasm #IrrationalEnthusiasm

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Maximizing compute performance requires collaboration. Jeff Wittich joined The Yotta Podcast to explain how Ampere is approaching the digital infrastructure’s silo problem, why we are urging the industry to go #GPUFree and more. Hear the convo. https://lnkd.in/gpyEjX4C

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⚡ Kicking off 🌎 Earth Day with exciting news as we unveil 8090 Industries' latest investment in Exowatt led by Hannan P. along with Sam Altman Andreessen Horowitz, Atomic, Overmatch Ventures, Protagonist, and many more. As the boom in AI heightens the energy demand for data centers, Exowatt is pioneering a fundamental breakthrough in baseload renewable energy that helps makes $0.01 per kilowatt-hour, 24 hours a day a reality for commercial and industrial use cases. 🏗 How does it work? The Exowatt P3, represents a breakthrough 3-in-1 modular system, a heat collector, a heat battery, and a heat engine capable of providing dispatchable power and heat 24 hours a day. Unlike traditional solar panels that convert sunlight into electricity directly, Exowatt uses a unique approach by storing solar energy in a thermal battery, which can retain this energy for up to 24 hours per day. The Exowatt P3 modules are designed to fit the space of a standard 40-foot shipping container. They can be deployed on small and large commercial and industrial projects, linearly scaling with workload size and infrastructure requirements. Best captured by Founder and CEO Hannan P. himself, an industrialist you're going to want to pay close attention to: “You don’t have to go back to fossil fuels to solve the data-center energy problem…That’s counterproductive and unlike traditional renewable solutions that require significant upfront costs and extended setup times, Exowatt's modular system can be deployed rapidly and cost-effectively – and it's available THIS YEAR. Exowatt is built to respond quickly to the escalating energy demands of the modern world, especially those spurred by the rapid growth of AI." 👀 Who Cares? Exowatt has a backlog of demand for OVER 500 megawatts for data centers across the U.S. and plans to begin deployments later this year. With this $20 million seed funding, Exowatt intends to expand its team and deploy the Exowatt P3 with its first set of data center customers. Stay tuned! Lots to come! cc Kerem Ozmen Wes Mendenhall Filip Vurdelja Haluk Sabanci Dincer Grant Brown Ishan Meswani Garuth A. Andrew Irwin Charles Oppenheimer Fatimah Bello #energyabundance #decarbonization #climatetech

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I find it hard to believe that with millions of EVs entering the market and the proliferation of AI compute that PGE is actually going to have excess capacity in 2040 without any additional generation from 3rd parties. I am also curious if there are enough transmission lines and if PGE views that as someone else’s problem. Maybe they are planning on AI and ACTUAL figuring it all out! https://lnkd.in/gybsMmaw

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SoftBank's Arm plans to launch AI chips in 2025 "SoftBank plans to build data centers equipped with homegrown chips in the U.S., Europe, Asia and the Middle East as early as 2026. As data centers require huge amounts of power, the company will branch out into power generation as well. It is planning to build wind and solar power farms, with eye on next-generation fusion technology. The group announced a plan in February to establish a robotics joint venture with a unit of Saudi Arabia's sovereign wealth fund. Mergers and acquisitions are also being pursued. Including its own funds and investments from sovereign wealth funds and others, with total investment is expected to reach 10 trillion. SoftBank has switched mainstay businesses in the past to keep up with technological advances. It operated an internet business in the late 1990s through a joint venture with Yahoo of the U.S."

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This analysis, at least anecdotally makes sense to me. In many situations, infringe and holdout is the least painful option for large infringers. The system enables it. - The plaintiff must allocate the time and $$ to assert, taking time and $$ away from selling and developing products. Even if they engage litigation financiers they are limiting their upside potential. - The infringer continues to infringe while employing stall tactics or simply relying on the painfully slow, overburdened legal system. - The cost benefit analysis for infringers - "infringe and pay lawyers" typically outweighs the cost of design around or license. - Enhanced damages and injunctions are rare. - Litigation insurance products reduce risk all around. "The Marcum report shows that there is indeed something wrong with the patent system in the United States but it’s not excessive litigation or patent trolls. The real problem is the inability of patent owners to enforce their rights against infringers. Given the difficulty of obtaining injunctive relief and the limited enhancement of damages, it is unsurprising that predatory infringement has become a standard business practice when, at worst, all an infringer can be expected to pay is a reasonable royalty and, at best, nothing at all."

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Portfolio management like this needs to happen more often. Note the use of an embarrassment clause of nearly 1/2 $billion if PE achieve certain IRRs on exit. #divestment #PE

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Founderville believes one of the most significant opportunities is emerging in legacy system applications. We look for manual tasks to leverage AI for efficient automation. Rather than chasing massive TAM, which will be addressed by larger VCs, we focus on smaller market domains that won't be chased as hard. Think of "boring" processes that require human intervention or manualized tasks. Those are opportunities. Keep your eyes open if you have deep domain expertise in a non-automated and fragmented industry. #entrepreneurs #venturecapital #startups #saas

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COMPUTEX TAIPEI = AI = Scaled Compute = Co-Packaged Optics Interconnect = RANOVUS Inc. @ Taiwan Today's GPU providers scaleout their Compute with copper interconnect technologies which limits their capacity. I had the opportunity to share some of our achievements and roadmap items with the COMPUTEX TAIPEI/InnoVEX audience around the next generation of Compute scaleout technologies this week. With the introduction of UALink (scaleout) and UltraEthernet (scaleup) standard groups, the industry is poised to bring high bitrate Ethernet connectivity (100/200/400Gbps per lane) as the backbone of the AI hardware infrastructure. https://lnkd.in/gHcrKPGa #SIP #CPO #AI #GPU #scaleout #scaleup

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On the latest Vital Signs, Nikhil Krishnan and I had a ton of fun chatting with Dr. Atul Butte. Dr. Butte is a professor at UCSF, Chief Data Scientist of the UC Health System, and a co-founder of numerous healthcare startups. In our conversation, Dr. Butte shared his takes on healthcare AI opportunities, challenges, hype, and more. A few highlights: ⚡LLM use cases, data, and growth LLMs are already helping to solve the “drudgery” aspects of medicine, such as automatically drafting SOAP notes and patient messages. Dr. Butte is excited about future applications of LLMs that can help with the “cognitive” aspects: with difficult medical problems an LLM might be able to stitch together disparate pieces of information to generate a potentially novel solution. He also highlights that prompt engineering will become the next “coding language” as so much of leveraging LLMs is knowing how to ask them the right questions. Additionally, Dr. Butte discusses how since 2016, UCSF has been working to deidentify its patient notes so that it can query them to answer clinical questions and ultimately enhance patient care. ⚡The need for patient-facing AI As patients are increasingly able to access their own personal health data in nicely structured formats (e.g., EHRs, wearables), they desperately need more tools to help them interpret and make decisions using that data. Dr. Butte understands that these patient-facing solutions are challenging to get funded but he emphasizes that patients need to receive the benefits of AI sooner. ⚡Evaluating healthcare AI solutions In order to evaluate AI solutions, we often put human specialists – such as medical professionals – on the same tasks. Understanding that specialists often disagree with each other, a significant challenge arises in figuring out how we can evaluate AI considering we can’t just “average” all the specialist opinions. Dr. Butte points out that there still remains a massive gap in AI evaluation tools. Additionally, there are so many organizations that want to have a say in how healthcare AI is regulated that the landscape is uncertain. An awesome conversation with an expert on all things AI meets healthcare. Listen to the full episode below: Spotify: https://spoti.fi/3Wr3643 Apple: https://apple.co/4acwgan

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Key takeaways from VC Goat - Vinod Khosla podcast. - The firm cares more about working on interesting problems with large technical solutions rather than just maximizing IRR. The team is there because they believe in the mission. - Khosla assumes they've lost the money the day they invest, and then maximizes for the upside opportunity. He calls it "option value investing" rather than IRR investing. - Khosla has contrarian bets in AI (neuro-symbolic computing, probabilistic approaches), biotech, robotics, crypto, and more. - He believes aviation fuels, fusion energy, new transit systems, and other contrarian areas ignored by most investors will be huge opportunities. - Most large innovations come from outsiders, not industry insiders. Khosla looks for founders who can learn a business rapidly rather than have deep domain expertise. The Future Impact of AI - AI will be deflationary and increase productivity growth to 4% annually vs the typical 2% forecast. This will cause great abundance but also increasing income inequality. - Bipedal robots will take over most manufacturing and manual labor jobs within 20-25 years. This will free humans to be more creative and pursue their passions. - Education will shift from job training to creativity. Uniquely human elements like taste and curation will be most valued in an AI-enabled world. https://lnkd.in/gqBsmbks

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Excited to share Marathon Venture Capital's investment in Eva Magnisali's DataForm Lab! Construction is large enough to be measured in GDP terms, yet remains a laggard in the adoption of automation. Our buildings are still constructed manually! Offsite manufacturing, i.e. assembling buildings in factories, provides the perfect canvas for putting automation to work – still, however, robots are nowhere to be seen... Eva studied architecture and robotics, and worked with design firms, developers and industry vendors, realising first hand what's keeping the industry stuck in the past. Then she got to work... Dataform Lab's software platform translates designs to production drawings and machine code, along with optimising processes and scheduling, essentially offering a modern operating system for construction factories. The company already works with some of the most prominent offsite manufacturers worldwide. Today it announces the completion of a GBP 1.1m Seed round led by Marathon. Eva and her team are on a mission to drive automation in offsite manufacturing. If you are excited about working at the intersection of technology and construction, get in touch! Building construction has been slow and expensive for far too long. Our next homes and schools may come from fully-automated factories, delivered at a fraction of today's time and cost. Keep an eye on Dataform Lab! https://lnkd.in/dVVfnudS

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NVIDIA stock increased 338,850% since IPO and is now the world's largest company by mkt cap ($3.35T). It wasn’t easy. Jensen Huang shares the most important thing when building a company: "...The company building process is mechanical. It's interesting. Lots of trial and error. It's organic. People matter. Personalities matter. ...And then I would say probably the most important thing is to realize that when you're building a company and a product, skill matters. Intellect matters. Training matters. But it's not enough. The part of it that is important to realize about building companies is that it's a challenging and painful and oftentimes extraordinarily scary thing to do. And so unless you have passion, unless you really love the process of building the company and what you're trying to do, it's going to be incredibly, incredibly challenging."

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