The Age of AI Podcast Aman Y. Agarwal

Have you ever had difficulty understanding what someone was saying because of their accent?

Do you have an accent that others don't understand, or hold biases against?

As a speaker of many foreign languages, I've always found it to be a very fascinating process. Ask any foreigner in your country about their relationship with the local language, and you'll realise how the topic is packed with various emotions.

But as it turns out, AI can help us communicate perfectly with each other in spite of thick accents.

My guest Ganna Tymko is the CEO of SaySo, which uses AI (specifically deep learning) to transform heavily accented speech into standard English (i.e an accent from Britain, America, etc) — in REAL TIME, as you speak!

Just imagine how it would transform cross-cultural and cross-border communications! We dive into the technology and business aspects:

00:23 - Why Aman is getting desensitized to accents

04:53 - Why we struggle with accents

13:59 - AI projects: research VS design

23:13 - How Sayso's tech works

33:23 - How our mouth muscles get trained to produce accents

41:48 - Taking accent transformation tech to the market

47:06 - When training ML models for humans, use human metrics

51:05 - Closing

"Tech Fluent CEO" for non-technical entrepreneurs: https://aman-agarwal.com/tfc/



A few years ago, DeepFake technology appeared on the horizon.

It allows you to take  a person's video and voice recordings, and create a digital "avatar" that you can use forever. We saw synthetic videos of political leaders and celebrities saying things they had never said in real life, but which looked so real they were indistinguishable from the real thing.

While many were concerned, others saw a more ethical potential –making unlimited videos with "AI models," by simply giving them a script to recite.

One such company is Colossyan, and in this episode I sit down with their CEO Kristof Szabo to discuss how they're dealing with the technical and non-technical challenges of building such a unique, AI-first product.

This is an example of a product that would be unimaginable a few years ago, but which will be virtually everywhere in the future. AI celebrities (which do not exist) are already taking over social media and have scores of ardent fans.

Personally, I can imagine a world where 90% of actors in movies are not real human beings, and where almost every movie you see is "animated." Not sure if that's what will happen, but it's a definite possibility.

Here's what we discussed:

2:01 – Who are early adopters for a technology like this?

7:16 – Challenges in building the technology; what makes it so hard

13:08 – Why the "secret sauce" matters less than the product roadmap

18:00 – How to recreate body language for an AI avatar? (Also, Aman makes a non-European joke)

22:30 – Colossyan's origin story

27:00 – Lessons from talking to customers

31:36 – Fundraising cycle and product-led growth

37:00 – How to keep research and product teams in harmony

42:23 – Crazy idea: doing away with the "ML team" in an AI company?

46:48 – (Allegedly true) story about Kayak

(Ethics Policy: These opinions are 100% my own as an independent observer and educator. I don't own stock in guests' companies or their competitors, nor do I get paid by them in any form for any reason at the time of publishing, unless specifically stated. Episodes are also not intended to be an automatic endorsement of any company or its products and services.)

You know that the future of transportation is electric, and that future is already here, but it's not "evenly distributed" – some countries, companies, and people are making faster leaps towards switching away from gasoline than others.

For companies that operate a lot of vehicles (in transportation, municipal amenities, retail etc), it turns out that switching to electric vehicles is more complicated than it sounds. Which cars do you switch first, which drivers do you allow to drive them, etc.

It's a niche problem, but it's growing, and today I speak to an entrepreneur whose company is dedicated to solving it – and their solution uses AI!

My guest was Mateusz "Mat" Maj, the CEO of VivaDrive, and in this episode we chat candidly about all the different aspects of managing fleets of vehicles.

1:26 - What are green fleets?
2:30 - Why European companies care about having green fleets
4:45 - Building a "digital twin" of a company
11:20 - Using an AI system to improve car fleet operations (in-depth reveal)
20:30 - What an "AI fleet manager" does: big data vs ML
25:00 - Using ML to upgrade to green cars
29:20 - Why is it complicated to switch to electric cars?
38:00 - European power grids aren't ready for electric cars
41:00 - How VivaDrive approached their go-to-market strategy
48:10 - Fundraising strategy (and how they chose it)

The manufacturing industry is as diverse as the number of products in the market.

There’s always a never-ending journey to do things better. And one of the key "things" is quality control and safety-critical inspections.

Inspections are quite labour-intense and expensive, which makes them very unscalable. The way companies have gotten around this so far is by sampling a tiny few of the products and look for defects, and then extrapolate from there.

But with AI, there's a better way. Humans don't scale, but AI does.

Which brings me to my guest Christian Els, the CEO of Sentin AI, which provides software for AI-powered inspections in manufacturing.

But manufacturing is often considered one of the most conservative, slow-moving industries (factories are expensive and don't change processes easily). There’s all this buzzword bingo about “industry 4.0” and smart connected factories, but very little light on how you actually connect and upgrade factories.

In this episode we drop the buzzwords, discuss the current REALITY of smart factories, and also share honest, no-BS lessons from the process of transforming them:

00:30 — Most powerful use cases for visual inspections with AI, and why it's needed

13:10 — In-depth breakdown of the process of bringing AI to a factory

23:20 — Challenges in convincing conservative customers that AI is a journey

26:30 — Cultural differences between old-school engineers and the new cloud culture

31:00 — Why Sentin doesn’t believe in 100% self-serve AI tools for customers

33:00 — Current state of IT systems in most factories, from Christian’s perspective

40:00 — Hard-earned lessons from selling AI transformation

46:00 — Navigating the complex competitive landscape for AI and computer vision in manufacturing

56:00 — Christian’s view of predictive maintenance solutions and their claims

(Full episode with VIDEO on: https://aman-agarwal.com/age-of-ai)

(Ethics Policy: These opinions are 100% my own as an independent observer and educator. I don't own stock in guests' companies or their competitors, nor do I get paid by them in any form for any reason at the time of publishing, unless specifically stated. Episodes are also not intended to be an automatic endorsement of any company or its products and services.)

For most people, "health" is not something you can measure, and nutrition and medical therapy are two different things — you try to "eat healthy" as much as you can, and get treatment from a doctor when you're "sick."

But there's also a middle ground where you can cure or reverse certain issues just by changing your lifestyle, such as food, sleep and exercise.

So how does AI come into this picture?

My guest is Dominik Burziwoda, CEO of Perfood — which uses AI to continuously monitor blood glucose levels and a host of inflammation markers, thus being able to give patients precise alerts and specific recommendations on which behaviours are most healthy to them.

Interestingly, they sell this technology primarily to insurance companies instead of direct to consumer!

We sat down to break down the science, technology, and business of glucose monitoring, as well as other challenges and noteworthy developments in the healthcare space.

If you're serious about health, fitness or technology, be sure not to miss this episode! (Full post on: aman-agarwal.com)

00:19 — A new paradigm of “digital therapeutics,” using AI for nutrition vs prescription

06:30 — Tracking inflammation and other biomarkers in your blood (correlation with continuous glucose monitoring, time series)

09:20 — How Dominik reversed his path towards type-II diabetes without drugs

13:00 — How Perfood's AI system recommends which foods to eat and which behaviours to change

19:00 — The challenge of "describing glucose curves" and why it's Perfood's core IP.

24:30 — The evolution of glycemic monitoring technology

38:00 — Regulatory expenses for digital therapeutics, and making them "clinical grade"

43:00 — Why breast implants transformed EU regulations

51:00 — Perfood's unique distribution strategy and 3-fold marketing (insurance companies, physicians, and patients)

59:30 — Innovation cycles in pharma vs digital therapy, and the changing landscape of European VCs

1:04:00 — Near-future outlook on the medical industry

There’s an overwhelming explosion of AI products and APIs these days for so many audio-visual content tasks — be it voice recognition,  transcription, translation, facial detection, etc etc.

If you’re a company trying to use as much AI in your company as possible, you could either build these yourself, or buy ALL these tools separately, OR…. the most convenient would be to just use one API/tool that combines them all under the hood, which is what we’re going to talk about today!

My guest was Eugen Gross, CEO of aiconix. They act as a single platform for as many state-of-the-art ML models and APIs (offered by all the top providers from Google to  Baidu) so that you only have to deal with one company for all your ML needs.

What I really like about their product is that it can intelligently combine the results from different providers (say for real-time translation)  and give you the most accurate result. They’ve even been used to transcribe Angela Merkel’s speech on live TV in Germany.

But building such a company means you’re almost offering hundreds of products and services from the start, so I was curious how Eugen’s team went about their business development journey.

As always, I bring you the most thorough and insightful discussion on the topic than anywhere on the internet:

00:30 — An easy tool for AI-enhanced digital content
06:30 — How Aiconix encapsulates both 3rd party and proprietary ML models
15:00 — Aiconix’s business structure: billing and services
19:30 — Sales strategy learnings: Work directly with end customers or sell to software developers first?
24:57 — Turning away customers and refusing to build certain things
27:51 — Journey of the company and accidental pivot during Covid
32:45 – Aiconix’s unique fundraising journey with both public and private money
41:21 – Standing out in a crowded market of AI tools
43:15 – Being a sales-driven or product-driven company?



Learn more on https://aman-agarwal.com/