• William Tunstall-Pedoe co-created Amazon Alexa after Amazon acquired his startup, Evi.
• He said the AI singularity is not here and finds the idea unlikely.
• He said this is because AI lacks the discovery intelligence humans have and is trained on human data.

This as-told-to essay is based on a conversation with William Tunstall-Pedoe, a 57-year-old founder and CEO who sold his voice recognition company Evi Technologies to Amazon in 2012, becoming a co-creator of Alexa.

Business Insider previously interviewed Tunstall-Pedoe about how Evi, an AI-powered search engine that answered spoken or typed questions, became an integral part of Amazon's Alexa. He told us his addiction to tech started in his high school and that early in his career, after graduating from Cambridge in 1991, he worked for Acorn Computers and the Isaac Newton Institute, where he did what he called "some more niche AI things." After leaving Amazon in 2016 to mentor founders and invest in AI startups, he launched UnlikelyAI, a neurosymbolic AI startup, in 2019.

Tunstall-Pedoe weighed in on OpenAI CEO Sam Altman's recent claim on the "Relentless" podcast that "we are now, like, in the singularity" — the point at which AI surpasses human intelligence and begins advancing faster than humans can predict or control.

This essay is part of Business Insider's coverage of expert responses to Altman's claim. It has been edited for length and clarity.

All sorts of friends of mine who aren't in technology have been reaching out to me over the last few weeks because they're suddenly having to wake up to what's happening at work or in their industry due to AI.

The number of people using LLM chatbots for all sorts of things is only growing, and people are becoming more aware of this change. Still, there are a lot of assumptions about AI singularity and what it means.

To me, the singularity is the idea that technology accelerates improvements in technology at an ever-faster rate. Eventually, it'll get to the point where the speed of technological change is so enormous and autonomous that the human race will get caught up in it and land in some magical future state.

AI is certainly continuing the trend of new technology accelerating old technology, but that's been happening for centuries, with the Industrial Revolution being a prime example. As we've seen in the past, it's not a new and novel idea for a machine to be better than humans at a task.

I think the idea of runaway AI, brilliant and perfect at everything and at a level of intelligence that's thousands of times ahead of what we see today, is implausible at the moment. I don't think we're in the singularity.

Machines have outperformed us in some tasks for decades

If you look at what the brain can do, there are things that computers have been able to do dramatically better than the brain for decades and decades.

If you think about math, people long ago stopped trying to compete with computers at math. If you think about memory, Google has perfectly learned hundreds of billions of webpages and can produce them on demand. Meanwhile, the human brain struggles to remember six or seven digits a lot of the time.

In some dimensions, LLMs are now superior to the human brain. They can talk competently on almost every academic subject, which no human being can do. They've learned competencies from large amounts of training data that cover a wide range of tasks and topics.

My point is, there are ways in which machines have been dramatically superior to the human brain for a long time; this isn't something brand new to worry about.

AI functions on human data

Part of the illusion of LLMs' extraordinary capabilities and why they appear so smart is that they've been trained on a meaningful percentage of everything that's ever been written; they've seen, read, and learned so much from training data.

But much of what we're seeing is based on the imitative capabilities that come from AI training on large amounts of data and a wide range of human actions. I don't think AI singularity is a natural continuation of that.

AI would need to show stronger evidence of what I call discovery intelligence: AI independently producing and evaluating genuinely valuable, paradigm-shifting ideas. LLMs can currently generate novel ideas, but they can't determine whether those ideas are realistically super valuable.

The singularity idea, to me, assumes that discovery-type intelligence is an extension of the learned-competence type of intelligence that AI already has.

Here's what I think we'd see if AI reached the singularity moment

If AI ever gets good enough to self-improve, actually innovate in AI, and it turns out there are no limits to its intelligence, then that would clearly be a very momentous point in time.

AI would then become extraordinarily capable very, very quickly because it will be able to keep improving itself in inventive ways. That rapid pace will be the singularity moment.

Generally, I think it's easy to critique the idea of the AI singularity because it kind of assumes reality is like a mathematical function and that intelligence is very linear. I think intelligence is a collection of things that you can do to various degrees of capability, so it's not clear to me that there is such a thing as runaway infinite intelligence, and I don't think true AI singularity level acceleration will happen.

We would recognize it if it were here

I don't think technology necessarily accelerates very smoothly. It accelerates for a bit, hits a wall, and then there's a decade or two before the next paradigm shift or the next big innovation unlocks further innovation.

I think even non-tech people would notice the difference between the rapid acceleration in adoption happening now and what would happen if the AI singularity ever comes. It would show up in pretty much everything.

• UK-based business owner Sean McDonnell relies on AI for his web design business and SaaS website.
• The White House ordered Anthropic to cut foreign access to Fable 5 while McDonell was mid-task.
• McDonnell emphasizes importance of backup plans due to AI tool disruptions like the Fable incident.

This as-told-to essay is based on a conversation with Sean McDonnell, 43, who lives in England. McDonnell is the founder of the web design company Kaizen and the SaaS website Consigns. The following has been edited for length and clarity.

Developing my website would not have been possible without AI.

I started my web design business earlier this year, which also led me to create a website that provides software to help companies track their waste. I run both of these ventures with my partner, and we enlist contractors for some operations and software development.

We're a small team, and AI tools are a big help. Last week, I saw a few posts online showing the amazing things that Anthropic's new Fable model can do.

I was keen to try this new technology, but didn't get much of a chance to use it. A few hours in, I was mid-task when the US government forced Anthropic to cut off foreign access to Fable with little to no notice.

The rug got pulled from under me pretty quickly, but because I was well-prepared, it didn't have a hugely disruptive impact on my business. It's a reminder that you can't rely too heavily on AI as a founder, and you should always have a backup plan in case of unforeseen circumstances.

I was keen to give Fable a try, but it was short-lived

I like using OpenAI's Codex for repetitive, code-intensive work, and Claude for tasks that help design the product's aesthetics. AI has been able to completely change the architecture of our codebase in a day, whereas a task like that would've taken a developer weeks to do manually.

After seeing so much about it online, I wanted to use Fable to conduct a full review of our product for safety and security flags. The model was in the middle of making some key changes to our codebase when it got shut off instantly with a notice saying, "Claude Fable 5 is currently unavailable."

I didn't realize until the next day that this had happened because the US government ordered Anthropic to block foreign access to the model. It's been a bit of a bummer, and I feel bad for the people at Anthropic for making a brilliant product and having the rug pulled from under them, too. I'm also quite annoyed we didn't get to do more with Fable. I think it could've propelled us so much further.

Being prepared helped us avoid a huge disruption

This isn't the first time we've had issues with using Claude. In the past, when we used Opus 4.6, it would stop mid-task because it hit the token limit so quickly. We didn't realize how token-heavy the tool was, and it left our codebase in a bit of a mess.

Because we'd learned this lesson with 4.6, we made sure we were more prepared for unforeseen circumstances with using AI.

When we started our product review last week, I asked Fable to create a guide that both Claude or other AI models could follow. This enabled us to pass the remaining tasks to other agents when we lost access to Fable. We passed some to Codex and others to Claude 4.8. If we hadn't been prepared this way, the Fable issue could've resulted in lots of work being out the window.

Fable getting pulled didn't have a major impact because we were ready for it, but it ruined our momentum. We're working on a deadline, and every minute counts, so delays like this can be quite disruptive.

Always have a plan B

This Anthropic incident has solidified my conviction that you can't depend completely on AI.

If the government were to shut off AI access completely, our business wouldn't end, because we've already built out our platform, but we are quite dependent on AI. A situation like that would likely increase our costs, partly because we'd have to switch to the old-school method of hiring developers.

In today's AI era, it's important to always have a plan B. Don't just rely on one AI tool. It's good to understand the strengths of different models.

Make sure you're documenting things as you go by keeping records that exist outside your AI tool. If Claude knows all about our code base, but it gets pulled tomorrow, would I be able to give that over to a developer? At this stage, I think I could, because I've been documenting everything as I go. It's a fail-safe.

A spokesperson from The White House told Business Insider, "The Trump administration is collaborating with AI industry leaders to balance cutting-edge innovation with national security concerns that affect both the United States and our allies."

Anthropic did not immediately respond to requests for comment.

Do you have a similar story to share? If so, you can reach out to one of the reporters at aapplegate@businessinsider.com and ccheong@businessinsider.com.

• Marie Pabelonio, a Google editorial lead, graduated from college with an English degree in 2009.
• She highlights the value of her English degree in adapting to AI's impact in the tech industry.
• AI helps her meet deadlines and focus on the bigger picture, but a human touch is still essential.

This as-told-to essay is based on a conversation with Marie Pabelonio, a 38-year-old editorial lead at Google, based in the Bay Area. This story has been edited for length and clarity.

I've been at Google since 2019, and as a writer, I knew AI would affect my role.

Looking back on my career trajectory, it feels like nothing short of a miracle that I ended up where I am. I graduated with an English degree in 2009, right after the financial crisis, and I'm now an editorial lead in people operations at Google, where I co-lead a small team that drafts and editorializes about 4,500-plus pages of HR policies. I've used AI to automate processes, refine drafts, templatize, and meet deadlines that would be impossible otherwise.

At this point, anyone, regardless of whether they're a writer or not, has felt it: Is AI going to automate me? Is it going to eventually just replace my job? I don't think I work more or less because of AI; I just work very differently.

I was a humanities major and fell into Big Tech

The job market felt very volatile when I entered it, which I think a lot of young people entering the workforce today feel.

I didn't have a career plan. I was an English major because I loved reading and writing, and if I found a job where I could do that and build a specific skill set on top of it, I would be OK.

My first job was as a fact-checker for the publishing arm of an industrial supply company, and then I became a copywriter in the advertising and marketing space. In 2016, I moved from Chicago to the Bay Area and became an editor at Amazon's subsidiary, Goodreads. I stayed in the Bay Area and made my way to Google by 2019.

I wasn't surprised that AI changed my job right away

We've heard the word "unprecedented" so much in the last six years or so that nothing surprises me anymore, including AI.

My team works with stakeholders and policy designers to interpret and draft policies, whether they're return-to-office, hybrid work, or immigration policies. There are areas where AI is useful in our work, and the tool has helped us regain more strategic time by automating tactical parts of our process.

This includes training the AI on standard article structure, to include four sections like background, key details, process, and related resources, formatting consistencies, including where headlines, a bulleted list, or a table would be used, and five to seven non-negotiable details the user needs to know from the policy.

I think there's still a lot of room for that human touch in that process. Once I have the output, I spend my time on the more strategic pieces, like verifying tone and voice, determining whether the article actually achieves the user goal, and how it fits with the broader content strategy of other articles.

In our writing, the goal is to inject humanity and warmth as much as possible, especially when explaining human resources topics like an employee's health insurance, compensation, performance reviews, and career growth. AI can't do that by itself.

AI saved me when I had a tight deadline

Around the time we started using AI, I had a big project to update existing policies, and I was on a tight deadline. I spent a lot of time upfront strategizing about how I could use AI to accelerate my work and meet my goals.

To address the overwhelming number of first drafts, I used AI to template a structure for readability, created a checklist for tone, style, and quality, and because of that was able to focus more on streamlining stakeholder reviews to check for accuracy. I met my deadline with a few days to spare. This was when it clicked for me that AI was changing things in a huge way, when this deadline looked really impossible, and then it wasn't.

Still, there were many times I had to validate and tweak the outputs. I never felt I could use AI as my secretary and leave it alone to do whatever it wanted.

Studying the humanities gave me a particular edge in the AI job market

I think there will be more of a premium on how we think, not what we know.

When it comes to writing, it's about being able to articulate the reasons behind your choices. Why this phrase and not that? Why put this insight here and not there? There's a rationale behind your judgment.

In job interviews, the question of how you use AI at work will inevitably come up now, and your AI output is only as good as your input. Good writers can get better, but bad writers can get worse, and just because you're writing fluently doesn't mean you're writing well. Studying literature so closely helped me reflect more on questions instead of answers.

This is the time to brag about how you develop your own sound judgment and how you use that judgment in your AI inputs. As good as it is to develop hard skills, it's just as important, now more than ever, to focus on soft skills too.

Do you have a story to share about your writing job in tech or AI? Contact this reporter, Agnes Applegate, at aapplegate@businessinsider.com.