Interview with Miguel Jetté, Vice President of AI at Rev

Tell us about the business you represent, what is their vision & goals?

I work for Rev, a speech technology company that helps turn audio and video into more accessible pieces of media powered by both humans and AI. At Rev, our priority is harnessing the potential of the human voice. We’re not just a transcription company — we lead the speech technology industry by combining human expertise with the power of AI to make speech accessible and valuable. Our value lies in unleashing the power of speech, and we offer unmatched accuracy and scalability that elevates any video or audio operation.

Can you share a little bit about yourself and how you got into the field of artificial intelligence?

As a Quebec native, I experienced firsthand the disadvantages of language barriers. Because of this, I became fascinated with languages and learned how tech plays a part in lifting those blockers. I received my Master’s in mathematics and statistics from McGill University, then I went on to spend a few years as a speech scientist at Nuance.

Can you share any examples of successful collaborations or partnerships between AI specialists and other departments within your organization?

In my current role, we have partnered AI with both humans and machine learning. We created a new workflow between AI and humans, where our human “Revvers” provided feedback to our AI to help it learn how it can improve. Because of this, our AI transcription offerings hit a 92% word error rate (which is a huge success in our industry). We've also bundled our powerful speech AI models into an API so that our customers can customize their platforms however they see fit.

What are some misconceptions that you believe the average person has about AI?

One of the biggest misconceptions people have about AI is that it’s going to take over jobs. It’s not. AI is going to change the way we work, but it’s more of a tool than a replacement, taking repetitive and mundane tasks out of our daily lives so we can focus on what really matters.

At Rev, we often call AI a “co-pilot,” as it works alongside humans rather than taking over. AI is a tool to help us work better, not a robot that replaces us.

What advice would you give to someone wishing to start a career in artificial intelligence?

If you’re wanting to begin your career in AI, make sure you aren’t just jumping in on the hype. You must be passionate about what you work on and be honest with yourself on the why. The why is the most important.

Once you’ve determined your why, begin to do your research. Understand what problem you want to solve with AI, and what current technology exists that might become your competition. You’ll also need to stay up to date with the latest AI news by following AI blogs, newsletters, and tech news outlets.

For businesses looking to integrate AI into their workflows, they need to start with customer research. Understanding your audience, their issues, their wants and needs, and their wishes is a great first step. You can do this through secondary research, interviews, and focus groups. Use the information gathered from these processes to inform what AI you integrate into your company and why.

Would you like to share any artificial intelligence forecasts or predictions of your own with our readers?

We are forecasting an increase in AI intelligence. As AI continues to learn from all of us, it will be able to provide us with a more unique understanding of our common problems (as well as more accurate information overall).

AI techniques and research will continue to soar in the next couple of years. I anticipate a similar level of improvement in the classic speech AI problems like ASR (Automatic Speech Recognition), MT (Machine Translation), and TTS (Text-to-Speech).

A big part of this forecast includes expanding AI’s skillset within various languages. AI’s using reinforcement learning (like ours) will constantly be given feedback that will in turn let it understand all different types of human voices better.

In addition, we’ll start to see new techniques combining LLMs with traditional problems like ASR, MT, and TTS. And a lot more research in mega-multimodal models, which will unlock another big area of potential for voice applications and for the potential of voice in general.

In your opinion, what are the key challenges facing the widespread adoption of AI technologies today?

The main challenge, in my opinion, revolves around misinformation. There are so many companies peddling products that don’t live up to the hype. Some of the current technologies are potentially hurting our field and are actually on the verge of being dangerous to adopt.

There are very few people working on the reliability of these big models, meanwhile everybody is quickly adopting the technology. It's a dangerous mix.

Another challenge in adopting artificial intelligence across organizations is the rise of direct competition. The industry is growing at a rapid pace, and companies that want to get in on the action need to move fast to stay ahead.

Are there any books, blogs, or any other resources that you highly recommend on the subject of AI?

I highly recommend that people interested in learning more about AI check out the content from the leaders in the industry. For example, our blog is home to plenty of great AI content such as this breakdown on AI Trends. I also love reading the newsletters AlphaSignal and ImportAI from Jack Clark. Podcasts such as Bg2 Pod and Andrej Karpathy are great resources as well.

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