 |
|
|
|||||
With their drab gray suits and their Buddy Holly glasses, the so-called traitorous eight don’t look like revolutionaries. Given no context, you can imagine them occupying some kind of middle-management role at a small regional bank. And yet these are the people you can thank for the digital world. The eightwhich included Intel cofounder Gordon Moorehad departed Shockley Semiconductor Laboratory to found Fairchild Semiconductor, which soon became the world’s biggest producer of electrical components for computers. Many of its founders would, in turn, leave again to launch their own ventures. Many of these companies coalesced in the same areathe place we now call Silicon Valleycreating an ecosystem for innovation and technological development that endures to this day. Look again at that photo. Even with the suits and the glasses, these are arguably some of the most interesting and influential people that the technology industry has ever known. Even if you don’t know their names, and even though they have never appeared on the Joe Rogan podcast, they still have a legacy that endures to this day. The Power of Hardware On a personal level, I have always found hardware more interesting than software. There’s a joke that CPUs are just “rocks we tricked into thinking,” which has some truth to it. You can’t help but be amazed at the process that turns iron, copper, gold, and silicon dioxide into something that can run unfathomably complex mathematical calculations, play chess, and stream Netflix. And that’s before you take into account that even the most basic consumer CPU has billions of transistors, each measuring a fraction of the width of a hair. Perhaps the main reason I’m drawn to hardware is that it’s often easy to measure whether something is better than the thing that preceded it. With a tape measure, you can see whether one computer is smaller than another. You can calculate how many mathematical operations a CPU can perform in a second, or count the number of pixels on a display. You can measure its weight, or the heat it gives off, or whether one battery has a larger capacity than another. Hardware is clean-cut. Straightforward. Unambiguous. And these improvements aren’t theoretical, but are felt directly by the end user. When a physical object is meaningfully better, you can tell. If you have upgraded from an Intel to an Apple Silicon Mac, you know this. You probably remember what it was like when you ditched your bulky CRT monitor for an LCD flat panel. You know the difference between a computer with a mechanical hard drive and one with flash storage. Hardware is typically built with utility in mind. The old adage “hardware is hard” is true, but it neglects the fact that it’s also pretty expensive. You only really build something if you believe it’s better than the existing thing, and that somebody will find it useful enough to pay for it. Silicon Valley Needs to Rediscover Its Roots The modern tech industryespecially that which now occupies the same hallowed ground once trod by the treacherous eighthas become a shell of its former self. Techs innovations feel only marginally iterative at best. It is this that makes me nostalgic for the era when Silicon Valley was about siliconor, more specifically, physical, tangible objects that changed the world. And I believe it is an era that we can, and must, return to. The Silicon Valley of the late 1960s, 1970s, and 1980s was a glorious time of American innovation and engineering, where verifiable geniuses discovered the breakthroughs that allowed our current world to exist. The integrated circuit. The microprocessor. The computer mouse. It was an era when technological vision and clear-thinking business strategy combined to bring new inventions to a market, and then popularize them to a global scale. And in doing so, Silicon Valley changed everything. To be clear, I am not just talking about vision. I’m talking about hardware. The applications we will need to run in the future will require faster, better computers, and we need somebody to invent them. Faster, better computers will allow us to reclaim ownership of the tech we use, enabling us to finally break free of the cloud. It will help undo some of the disastrous cultural changes that have occurred over the past decade or so, when people got used to the idea that they must always be subject to the mercies of another, larger tech company. Hardware is hard. Change is even harder. But in this case, I think it’s worth it. The Bright Light on the Tip of the Spear So, there is some cause for optimism, and its not in giant GPUs. Buried in the news coming out of CES was the announcement of Nvidias DGX Spark, a $3,000 desktop computer powered by Nvidias GB10 Grace Blackwell Superchip, that went relatively unnoticed but I believe is a significant moment in personal computing. The DGX Spark delivers up to 1 petaflop of performance in a compact form factor, giving researchers and developers unprecedented access to cutting-edge computational power directly at their desks. Its like having a computer thats a thousand times faster than a regular desktop in the body of a Mac Mini, and Im a little surprised it isnt being taken more seriously. In more human terms, Nvidia created an ultrapowerful Mac Mini that developers, data scientists, and AI researchers are able to use to run reasonably large data workloads and AI models on their desk as opposed to a fleet of massive GPU servers in the cloud. While Silicon Valleys biggest companies have grown on the back of software, the truth is that it needs hardware to grow any further, and while those GPUs might be the headline-grabbers during Nvidias earnings, creating meaningful new kinds of computing is what will lead to actual innovation in software. As a result, by creating a Blackwell chip inside a Mac Mini-size supercomputer, Nvidia allows companies to crunch through large data sets or run self-hosted generative AI models quickly and efficiently, all without relying on the cloud to do so. This vastly lowers the barrier to entry for high-performance computing, which currently requires buying or renting expensive specialized hardware or spinning up expensive infrastructure. I’m going to dive briefly into why this matters. For years, both at Voltron Data and previously at BlazingSQL, I’ve advocated for clustering smaller, more efficient, and less-expensive GPUs together using high-performance networking. However, network limitations have always prevented full utilization of the cluster’s compute performance since data simply couldn’t move fast enough to keep GPUs fully fed. While it hasnt shipped yet, Nvidia has specifically called out the inclusion of ConnectX to allow users to connect two Nvidia DGX Spark computers together, as well as other features (NCCL, RDMA, GPUDirect storage) that are specifically built for faster networking. This will enable efficient parallel processing and high-bandwidth communication, making high-performance AI and analytics workloads accessible to a broader range of researchers and enterprises. A distributed model using a cluster of Nvidia DGX Spark units could offer a more cost-effective and flexible alternative to currentl available GPU clusters, lowering the barrier to entry for basically any high-performance computing use cases. My focus on Nvidia DGX Spark is to illustrate a greater point about what will keep Silicon Valley at the forefront of technological progress. True innovation doesnt come from just making things bigger or more powerful, but in the distinct relationship and interactions between software and hardware, and even between different pieces of hardware. Nvidia DGX Spark isnt just Nvidia making a chip smaller, but finding ways to add faster on-device memory, software to make getting the data to both the memory and the GPU faster, and (I imagine) some unique ways to keep it cool. The truly world-changing innovations and technological breakthroughs that will advance humanity will come from a deep commitment to silicon engineering, and Silicon Valley needs to remember that this is the only way that software will continue to grow.
Category:
E-Commerce
Todays B2B CEOs are tasked with a delicate balancing act: driving growth, improving efficiency, and creating seamless customer experiences, all while navigating unprecedented market complexity. Meanwhile, the revenue professionals responsible for executing these goals face their own challenges. Buying journeys have become increasingly labyrinthine, with big buying teams and long sales cycles. Seventy-seven percent of B2B buyers say their last purchasing decision was very complex or difficult, with more than 800 interactions on average with potential vendors. Misalignment across revenue teams compounds the issue, making it nearly impossible to deliver efficient, relevant, and cohesive buyer experiences. This complexity creates a cycle of inefficiency, where teams work harder to achieve diminishing returns. Fortunately, were at a pivotal moment in technology. AI and data advances are empowering organizations to simplify complex revenue cycles. Among these innovations, AI agents offer a promising solution. AI agents arent simple software add-ons. Theyre intelligent partners that enable teams to act faster, collaborate more effectively, and scale more strategically. Lets explore how CEOs can equip their teams with AI agents to achieve sustainable growth. AI agents are partners, not tools AI agents represent a significant evolution in business technology. Unlike traditional software, which passively waits for human input, AI agents actively analyze data, surface opportunities, make recommendations, and drive results in real time. For CEOs, this distinction is critical. AI agents dont just automate repetitive tasks; they perform work that aligns with strategic goals. From identifying early buying signals to optimizing customer engagement, AI agents seamlessly integrate into workflows to ensure every touchpoint is efficient, personalized, and impactful. In a world in which breaking down silos and acting on intelligence faster than competitors defines success, AI agents are the bridge between vision and execution. Why good data powers great outcomes AI agents are only as effective as the data that fuels them. AI agents are built on large language models (LLMs) trained on public data. That data can sometimes produce sketchy resultslike when Googles AI search raised (and then dashed) Disney fans hopes by describing the impending release of Encanto 2 because it pulled its data from a fan fiction site. The fallout of misinformation in business can do much more damage than simply disappointing movie-goers. Poor-quality data can lead to disjointed recommendations and faulty business decisions. Not only that, but if you only use public data to feed your AI agents, you’ll have the same output as everyone else relying solely on LLMs. The solution for this lies within a businesss own walls. Enterprises have massive amounts of data that LLMs have not seen. Feeding this data to AI agents allows them to produce differentiated, contextualized output. For instance, integrating intent data into a sales-focused AI agents diet yields personalized outreach based on individual prospects needs. It’s also important that the data AI agents use is clean, accurate, and comprehensiveand that it spans the entire revenue organization. Shared data ensures that AI agents can piece together the full picture of the buyer journeyfrom early intent signals to post-sale engagement. What CEOs get wrong about AI agents AI agents are difficult to implement. AI agents don’t necessarily require complex overhauls. Scalable, modular solutions make it easier than ever to adopt AI incrementally, starting with specific use cases and expanding as success builds.Example:Many of our customers quickly deploy our conversational email agent for one-use case (such as re-engaging closed/lost opportunities) and build from there. This enables teams to see the immediate value of AI agent-led contextual email conversations, while at the same time laying the foundation for broader adoption. AI agents are only about efficiency. While AI agents excel at streamlining processes, their real value lies in their ability to drive strategic outcomes across industries.Example:Johnson & Johnson uses AI agents in drug discovery to optimize chemical synthesis processes. AI enhances efficiency, but more importantly, it drives strategic advancements in pharmaceutical innovation by accelerating development timelines and improving cost-effectiveness. The ROI of AI agents: Real-world impact Harri, a global leader in workforce management technology for the hospitality industry, faced a challenge familiar to many CEOsthe need to scale engagement without increasing resources. To support their strong marketing team in generating demand, Harri implemented an AI agent through 6sense as part of its outreach strategy. The AI agent autonomously identified high-intent prospects and delivered timely, personalized messages at scale, enabling Harri to engage buyers more efficiently and effectively. The results: They generated more than $12 million in pipeline and $3 million in closed/won deals in just one quarter. Campaigns achieved a 34% view-through-rate (VTR) rate, far exceeding the initial goal of 20%. They scaled marketing efforts without compromising on personalized engagement. By scaling outreach, improving engagement, and targeting high-value opportunities, Harri took pressure off its team, while achieving significant growth and enhancing the buyer experience. Pave the way for smarter growth AI agents are still so new that CEOs who arent using them yet can get ahead of the competition by learning to incorporate them now. These agents simplify complexity, align revenue teams, and deliver results. By integrating AI agents, CEOs can create seamless, personalized buying journeys that meet todays expectations while driving growth. With significant AI advancements ahead, having a clear strategy is essential. By proactively adopting AI agents, organizations can address challenges and position themselves for sustained success in a rapidly evolving market. Jason Zintak CEO of 6sense.
Category:
E-Commerce
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. Diversity, equity, and inclusion (DEI) are sometimes described as market distortion, inefficiency, or antithetical to meritocracy. Yet, we can see that equity-related initiatives have actually served our notions of meritocracy. Removing artificial barriers to hiring or investing in exceptional individuals is simply smart business. Cutting all things DEI from government may prove less smart, efficient, or efficacious. Barriers remain high for women, despite their advances. Women are outperforming men in so many areas. Since 2014, weve had a higher percentage of women who are college graduates compared to men. Increasingly, women earn the same or more than their husbands. And of course, on top of all of this, women continue to do the majority of household work within our homes. Equity means opportunity For some, this is a dire concern requiring new solutions for men to maintain ground. The emergence of the bro-verse is just one cultural manifestation of such fear. We also know that the U.S. president and conservative groups understand that gender roles are shifting because a large part of the presidents campaign was staked around this trend. Candidate Trump tapped into a fear and offered a shortcut, a leg up to individuals who arent receiving the same opportunities they once did (men), rather than relying on meritocracy to lift up those who deserve it. Others, recognizing the cost of lost potential, champion solutions that do not come at the expense of women. Whatever the motivation, we cannot claim that men are being left behindand something must be donewhile also dismantling diversity and equity programs across the federal government. We cannot recognize the value in helping certain groups and then say that targeted interventions designed for other groups are not necessary or might be harmful. Our very intention underscores what we know to be true. We are better when we remove barriers to full participation and remedy the effects of intentional and unintentional exclusions. Clearly, we understand that neither meritocracy nor efficiency can be achieved without our best contributors sidelined. Government investment needs dedicated public servants Consider Gladys West, PhD, a mathematician whose precise calculations of the Earths surface helped develop the technology we now know as the Global Positioning System (GPS). Her groundbreaking work was made possible through government investment and public service, as she played a critical role in the Navy developing technologies that benefit us all today. Many other technological advances that we cannot live without came from government investment. The obvious example is the internet, which was the result of a massive level of investment from the federal government. Elon Musk would likely have a different career without those federal dollars and Wests genius. Now I worry about who is being cut out of our federal agencies, all in service of efficiency and meritocracy. Who are todays innovators like West, who may not get a chance to invent the next revolutionary technology like GPS? If we truly care about meritocracy, we will stop this senseless disregard for talented, skilled, and knowledgeable federal public servants. We should ensure that those dedicated public servants especially women and people of colorcan continue their work building a better country for us all. Joe Scantlebury, JD, is CEO of Living Cities.
Category:
E-Commerce
All news |
||||||||||||||||||
|
||||||||||||||||||