AiThority Interview Series With Tuomas Rasila, CTO & Co-Founder at Vainu

The companies investing most of the money in AI are not actually AI businesses per se. The guys building the tools are not running the businesses.

Know My Company

Tell us about your journey into Artificial Intelligence and machine learning? Why did you launch Vainu Labs?

At Vainu, our goal is to understand everything ever written by every company on the Internet. Because of that, the amount of data we need to be able to process is insane. All the data is originally meant for humans to read. We are talking about unstructured textual content. Machine learning — teaching the computer by example — is the only solution at this point.

What is Vainu Labs and how does it leverage AI-ML technologies to work with data?

Our goal is to extract as much information as possible about every company online. We take solid facts that we can reflect on a single company. We leverage Machine Learning technology to understand and group unorganized textual content.

As a tech leader, how do you prepare for an AI-driven world?

We are constantly figuring out how to create pipelines to enable real human beings to provide us with answers we want from the data.

We can glean data from human brains. This is transferable to AI algorithms. By leveraging machine learning to complete human processes, we are preparing for the AI-driven world. In other words, we try to download the understanding of human brains and let humans instead focus on tasks where computers will fail.

We make sure we automate what we can automate today. Individual parts of tasks will be automated before the computer overloads.

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What message/advice do you have for young professionals looking to build a career in AI/ML?

Start by doing. All the libraries and technologies we are leveraging are relatively new. For example, Google’s TensorFlow (it’s open-source library for dataflow programming) is just a few years in the making. If you are a fast learner and eager to work, you can advance rapidly.

What is the state of ‘AI for Businesses’ in 2018-2020? How can business development teams better benefit from leveraging Vainu’s AI-powered platform?

The companies investing most of the money in AI are not actually AI businesses per se. The guys building the tools are not running the businesses. The major companies like Amazon, for example, are leveraging it and bringing on development teams who understand it. Companies with the most data and the most need for data processing are the organizations putting the biggest stake in AI-powered platforms. They have the data to make machine learning vital for them.

Vainu’s platform automates huge parts of the sales prospecting equation. Instead of performing manual searches in our platform, we are collecting examples automatically and explaining to our users why we are offering them new kind of prospects.

90% of Vainu’s business development is now driven by AI. AI makes the decision to whom we reach out to and when.

Read More: The Top 5 “Recipes” That Give AI Projects A Higher Likelihood Of Success

Tell us more about your AI research programs and the most outstanding digital campaign at Vainu Labs?

Vainu Labs’ experimental AI is currently driving huge sales teams in the telecommunications space. With A/B testing, we can prove significant results in predicting how likely the prospects are to convert to customers. This has been proven by real sales work.

Also, we have been able to predict reliably how many employees the company will have. We can predict the new type of technology they will buy.

What are the major challenges for AI technology companies in making it more accessible to local communities? How do you overcome these challenges?

One of the challenges is how much time is consumed to generate proper data to make predictions. The availability of data to predict is not there for AI. So, the lack of data is an issue. Cleaning up the data is also an issue.

Vainu’s mission since we started four years ago has been to collect data on real-world events. We’ve accumulated a ton of data because of that and stand on the greatest data set in the B2B space.

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Tell us “The Good, The Bad, and The Ugly” of AI/ML technologies.

99% of AI is being taught by data sets provided by humans. It is implemented in such a manner that it can never learn to become better.

In that sense, machine learning is still tied to limitations of human intelligence.

However, the beauty of this is you can combine hundreds of thousands of people’s insights into AI.

In terms of the ugly, AI has this kind of sci-fi, futuristic vibe for a lot of people. Many of the claims people make about AI are misleading or simply not true. Machine learning does a better job of explaining what tech leaders are practically doing to advance companies – teaching machines the tasks to perform.

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Would you agree that ‘Weaponization of AI” is a real danger? How steps do you take as a tech provider in preventing the misuse?

It isn’t a greater threat than weaponizing any technology. But weaponizing any technology is a serious threat to mankind. So much technology has already been wildly weaponized. The solution isn’t legislation. It is creating solutions that combat weaponized AI — it is about being a step ahead of weaponized AI and taking it head-on.

The Crystal Gaze

What AI start-ups and labs are you keenly following?

We are extremely interested in any company who can take complete human work to be fully automated with AI. For example, a company that can create a trading robot for a stock exchange. If you could take a complete job of a human being and have it driven by AI, that’s a real breakthrough.

What technologies within AI and computing are you interested in?

I’m interested in companies that can fully automate human tasks, freeing up the time for human beings to focus on things that computers are not capable of doing.

As an AI leader, what industries you think would be fastest to adopting AI/ML with smooth efficiency? What are the new emerging markets for AI technology markets?

Financial trading, stock markets come to mind.  I’m thinking about industries where the level of repetition is extremely high. For the field of sales prospecting, this could lead to companies with a high count of customers. For example, insurance companies, telecommunications, and banks.

What’s your smartest work-related shortcut or productivity hack?

Copy and paste from Stack Overflow is a gem for developers.

Tag the one person in the industry whose answers to these questions you would love to read:

Alan Turing (if I could go back in time and bring him into our era). He’s the famous mathematician who essentially laid the foundations for the concept of the modern computer.

Thank you, Toumas! That was fun and hope to see you back on AiThority soon.