Technology has changed how we do things, and now it addresses our needs even before we know they exist. Machines can now take care of menial chores and duties, and this technological advancement has changed every aspect of humanity. It’s already becoming a reality. Kevin Surace, an innovator in AI and robotics, is at the forefront of this technological revolution.
Kevin Surace, a pioneer of Silicon Valley and holder of more than 94 patents, is a guest on The Tech Visionary Show. He discusses the future of AI and automation and their impact on many industries, organizations, and societies.
He has a good combination of visionary thinking about the future and practical hands-on experience that has shaped the tech industry for years. He spoke of how all this started with the development of virtual assistants and went up to where we are now—how fast automation is coming in and what lies ahead.
In this article, we dissect some of the key themes raised with Kevin in this episode about work, the rush of new inventions, and the changes they are bound to create within industries.
Main Points
- Innovation Driven by Joy: Kevin Surace emphasizes that true innovation stems from joy rather than mere success. A positive mindset can inspire creativity and problem-solving, making it essential for tech industry leaders.
- The Evolution of Virtual Assistants: Kevin's work in creating the first virtual assistant laid the groundwork for modern voice AIs like Siri and Alexa. This highlights the importance of addressing real-world problems through technological innovation.
- The Importance of Software Testing: The article stresses the critical need for rigorous software testing to avoid catastrophic failures. Companies must prioritize quality assurance to safeguard against operational chaos.
- The Economic Impact of AI Productivity: Increased productivity from AI can lower costs and drive demand, ultimately creating more jobs. This highlights the potential for AI to be a catalyst for economic growth rather than a detriment.
Why Joy Equals Success
One of Kevin's first points in the podcast is deeply personal: joy equals success. This is something that Kevin would not take lightly. As a person who has been the CEO, the CTO, the futurist, and the inventor, Kevin has a very rare view of success. It’s no longer only associated with the trophies and the profits but more about the journey and the essence fueling creativity.
“I wake up every day with joy,” he states, clarifying that joy is not happiness. Instead, it’s the joy of knowing that today, you have another chance for something extraordinary to occur.
“And if the alternative to waking up would not be to bring joy, then I must be positive,” he stresses the dangers of negativity. Work for Kevin entails fulfillment, irrespective of how minor the effort may be, as there is always a point of success attainment.
This philosophy does not only relate to him: it is something that Kevin thinks every innovator, every very active leader, can adopt. It is a mindset that pushes you to resolve problems more insightfully and eagerly embrace every new problem. In the fast-paced world of technology, where new obstacles arise daily, this approach can be a game-changer.
The Birth of Virtual Assistants
Back in the mid-1990s, when Siri, Alexa, and Google Assistant were nothing more than dormant domain names, Kevin Surace was already crafting what would become the first virtual assistant. As he describes on the podcast, it was not about developing a cool new technology idea but solving people's real problems (how to manage their communication while driving).
We were receiving emails from all over the world at the time, and you couldn't access them while driving. I can move my mouth but I can not hold anything or pick it up,
Kevin says the real-world issue that inspired him to build a voice-activated smart assistant.
Kevin came up with a revolutionary solution. His team built "Mary," a conversational virtual assistant that could handle calls, emails, and even faxes using voice. Remember, this was when most phones had small displays and limited features. Kevin's solution was more of a vision towards the future, on the cusp of safety and accessibility, concepts that live at the forefront of AI development today.
But even more interesting is that Kevin paved the way for the virtual assistants we use today. Kevin pioneered the core ideas behind voice user interfaces, AI-driven responses, and task automation, which Apple would eventually license for use in their Siri virtual assistant and by other tech giants.
Phones back then had such small screens you needed a voice user interface. Everything stemmed from that,” he says. Nowadays, assistant services are all but everywhere, and a lot of Kevin's early innovations still live in the heart of them.
The AI Phase of Co-Pilots
Kevin picks AI up from the present and places it in its so-called “co-pilot” stage. Compared to their previous use, however, such tools have not yet reached full autonomy in most cases; instead, they act as assistants to the human operator in performing specific tasks.
AI co-pilots such as ChatGPT or GPT-4 find applications in writing, customer support, and many other industries. They help humans perform high-level thinking or more strategic tasks.
“AI helps us shed the tasks we don’t want to do.” Kevin also adds that because so many repetitive or simple jobs can now be performed by machines, people will be working on rather more exciting jobs. Not only is it great to be in that co-pilot phase of development since it is not only an idea in the laboratory anymore; it is embedded into most of the tools and systems used daily, increasing the efficiency of most firms.
Kevin further notes the exciting change that is coming with the use of AI in areas such as software testing. Previously, software testers had to write test scripts, execute them, and handle the existing bugs, which was quite tiresome and required a lot of time.
Now, AI can do most of this work, which shortens the time required and improves the efficiency of the entire testing process. “here are two and a half million people in that job, but AI can do these tasks much faster and better,” Kevin says.
But this push towards automation is a double-edged sword. On the one hand, it allows for business efficiency and cost savings. On the other hand, it raises concerns regarding job loss or displacement. Kevin is optimistic, though.
According to him, AI may displace some jobs, but it will also give rise to new roles and opportunities elsewhere, just as the Industrial Revolution did when it replaced agriculture or the computer made us obsolete. As Kevin points out, there is precedent for this type of change in technology leading to significantly more jobs in a parallel industry rather than fewer.
Driverless Cars and Human Joy
As the discussion shifts to transportation of the future, Kevin makes a shocking statement: in 50 years’ time, persons seated behind the steering wheel of a vehicle may be outlawed in certain places. He imagines a world equipped with AI technology; automobiles without human drivers will rule the cities, thus decreasing traffic accidents and time spent on the road for various vehicles.
Even though this may seem like something out of science fiction, people should be pleased to realize that companies such as Waymo can provide fully managed taxi services without any drivers present in the car, even in cities like San Francisco. This brings this vision into a more realistic context.
But what about people who love driving? Kevin acknowledges that for many, driving isn’t just a mode of transportation—it’s a pleasure, a hobby, even a passion. “There will be areas where you can drive to your heart’s content,” Kevin tells his listeners. Still, he insists that in the future, especially in densely populated urban areas with horrible traffic jams on every road, people will be prohibited from driving for safety reasons.
Kevin elaborates on the fact that the technology of self-driving cars will significantly enhance safety because the system in place can do better than a human in most explosive situations. “There will be a time when you’ll go, ‘I actually want the AI to drive,” he says, especially as we age and our reflexes slow down. So, using AI in this sense would reduce the risks associated with transportation and improve how we spend our time by minimizing stress and road accidents.
AI and the Trust Dilemma
Kevin shows logic in the discussion when he touches on the most critical aspect—trust. The more AI is involved in our daily lives, the more chances there are of making mistakes or encountering failures. Kevin tells a cautionary story about a software update by CrowdStrike that was never tested and whose implementation brought chaos to their system. This illustrates the need for software testing for AI designers.
“You saved a thousand dollars in QA costs but cost the world a hundred billion dollars,” observes Kevin, underscoring the high stakes in deploying untested software. Unarguably, while AI brings more efficiency to systems, it also brings new challenges. Without the necessary testing, AI systems can wreak havoc, from airline shutdowns to banking crises.
This makes one point very clear: how much trust should we place in AI systems, especially those about to hit the market? Kevin notes that while AI will likely improve over time, companies must have adequate measures to deter them from causing such problems. “No company should be touching the kernel without a large amount of testing,” he warns. In other words, as AI takes on more responsibilities, the need for caution and oversight becomes even more critical.
Productivity vs. Fear
Kevin's discussion naturally brings up the topic of fear. Many fear that the increasing use of AI will result in a loss of jobs and people becoming more reliant on machines. And while Kevin recognizes these fears, he remains optimistic about the future.
He explains, “We’ve been relying on technology to run our businesses for hundreds of years.” While new technology will always face hurdles, the advantages outweigh the negatives. Every technology, whether electricity, the internet, or now increasingly AI, has enabled us to be far more productive with our time, resulting in nothing but good for society.
Kevin encourages listeners to focus on the positive aspects of AI. The reality is that some jobs will be eliminated while others will be created, and businesses will generally become more effective in the process. “The more productive a companybecomes, the lower the cost of goodsand services, which increases demand and creates more jobs.” Kevin explains that AI-driven productivity can be both a long-term solution for economic growth and its primary catalyst.
The Biggest Challenge
When asked about the biggest challenge in AI, Kevin Surace points to the shortage of GPUs. These processors are essential for running AI models like machine learning and generative AI, which need massive computational power.
Without enough GPUs, AI's growth could slow. "There’s not enough GPUs, which is a type of processor that's needed for AI, and they're very, very expensive. Most of them come from NVIDIA," Kevin says. This reliance on one supplier creates a bottleneck, limiting AI's scalability as demand rises.
Kevin also highlights the huge energy demands of AI. As AI adoption grows, data centers need vast amounts of electricity. “We need huge operation centers that require immense amounts of electricity. You're talking about unbelievable amounts of electricity. For example, I need a nuclear power plant next to each operation center,” he adds. Without breakthroughs in energy efficiency, AI could hit a wall.
Another issue is how quickly AI is integrated into business without understanding its long-term effects. Kevin warns that businesses might overestimate AI's immediate productivity impact. “Everybody's used gen AI, and now the C-levels are saying, ‘Alright, I want to start measuring productivity increases if I spend this money.’
According to Kevin Surace, the hardest problem in AI is the shortage of GPUs. These high-performance computer processors are necessary when training AI models, such as deep learning and generative AI, which require tremendous computational horsepower.
This is important because "There’s not enough GPUs, which is a type of processor that's needed for AI, and they're very, very expensive. Most of them come from NVIDIA. "This single supplier dependency sets AI on an old-fashioned assembly line where only so many widgets can be manufactured simultaneously. Consequently, this creates scarcity, limiting its scalability in the market.
Kevin also stresses AI's massive energy usage. With the increasing adoption of AI and its requirements for enormous computational power via data centers that consume giant stores of electricity.
An important problem with AI is the speed of integration into business without considering its long-term consequences. Kevin cautions that businesses should not expect AI to affect productivity straight away.
Wrapping up
Kevin Surace's grounded perspective on AI, automation, and the future of work is based on his real-world experience. Although AI will undeniably replace many existing jobs and industries, Kevin believes it has greater potential for growth and innovation.
The message for businesses and people is clear: move forward but do so with intention. Keep testing new technologies, make sure they solve a real problem, and remember that your creativity and problem-solving capabilities cannot be replaced, but some tasks can be automated.
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