Slush lightened Helsinki up once again during the November darkness. For those who have not visited Finland during this time of the year: don’t. Unless you’re coming to Slush.

We, meaning the Aito.ai team, attended Slush during the 2 days, plus some of the many side events. Our main goal was to measure the temperature of the machine learning and database market. To test our sales and marketing messages live, and to get market feedback from tech-savvy startups. One question guiding us was "what would you do if you’d have an extra machine learning engineer in your team”. We were eager to learn what items do companies have on their AI backlog. By AI backlog items I mean those use cases which will need machine learning as an integral part of the solution. One repeated answer was striking, but at the same time describes well the state of AI adoption.

But first, a few words about Slush, Aito.ai and Finland to set the context right.

Pöhinä

The word describing the atmosphere around Slush is “Pöhinä”. A direct translation would be “fluttering for no particular purpose”. More commonly it means the buzz and hype you feel with all your senses at the event, the startup communities and the side events surrounding it. Pöhinä is contagious and during November there is an unspoken agreement that everybody is allowed to Pöhistä (verb). Even the communities and organisations who are usually very conservative and strict loosen their ties and start to talk wanna-be tech slang and sponsor Pöhinä-events for their peers.

For a startup, the Pöhinä is best described by the sound of pitches, laughter, beeping phone message, screaming, slogans on big, bigger, biggest screens and a fully booked agenda with meetings arranged through the matchmaking app. Enhanced with the challenge of attending as much as possible interesting talks, and being active on social media. Entrepreneurial energy meets technology-evangelists meets investors looking for the next unicorns, minicorns, soonicorns and decacorns.

If there are still cracks in this Pöhinä, they will be filled with the ones who offer the services for any of the ones mentioned in the previous paragraph to find the rest who have been mentioned in the same paragraph. Setup is complete with the perfect designs, visuals, music, layout and good catering.

Activist performance - Mykki Blanco at Founder’s stage during the afterparty

The program and events which are organized by the Slush gang (of which 2400 volunteers!) is awesome. Slush is filled with the authentic atmosphere of young and eager entrepreneurs. And spot on topical themes of morals and ethics. Slush is creating a vibrant atmosphere which is fully supporting (co-)founders to bring their message to the world.

Aito

Six persons of the Aito team attended Slush, but I’m here writing my personal summary of what stood out the most for me. I focussed my time mainly by talking to people, networking. The only presentation I was able to see was Eljas giving a demo of the Aito predictive database during the Showcase Studio demo, so that should say enough. And another one where I was participating at an AI panel discussion.

Eljas Linna demoing Aito for a huge crowd at Showcase Studio.

Aito, where I am CEO and co-founder, is a startup at the stage of validating the product-market fit. Our Predictive Database has a very promising start. We are 18 months old, but already have a production version, and some revenue as well. We have taken an own unconventional way to approach AI and machine learning which we are patenting. We believe that the power of ML should be available for software engineers instead of being a privilege for the few who have data science skills. We didn't spend too much time on finding new investors since we finalized our Seed round earlier this autumn.

Being in a relevant place to create impact

Why Slush matters? Why we selected to invest on it? First of all, the investment is relatively low since it is a local event for us. The organizers have different price ranges for startups, investors and media. Most of all, I know I would be meeting a large enough group of relevant people. Slush provides consistent quality with 25 000 participants who all want to learn about new tools and technologies.

Remember the Pöhinä. It was boosted this year. The leading Finnish newspaper Helsingin Sanomat was writing that “this year in Slush the investors have a crazy amount of money” (in Finnish and behind payment wall). In short, the expected values have been dropping in interest rate-, stock- and property-markets. So the risk investments to startups make a lot of sense since nothing stops the small and medium sized businesses - the backbone of the economy all over the world.

All the above adds relevancy of the event for a startup of our kind. Not only with the business logic, but the deep motivation to change the world to be a better place. Bringing enablers to the reach of who want to create real impact. And trying to reduce the amount of nonsense and even things which drive world to be a worse place. With delight we welcome the events where it is forbidden to share swag. I do not have any nostalgics thoughts for those exhibitions where I was ending up in a hotel room with a bag full of, well, nonsense.

Finland, Finland, Finland, the country where I want to be...

As Monty Python was singing on the common nominator of both Slush and Aito. However the Finnish attitude goes deeper than pony trekking or camping.

Last year the feedback to Aito in Slush was too many times “sounds fabulous and exactly what the world needs, but I do not really understand what you are doing”. This year, we have started to identify the sweet spot use cases in our focus domain such as churn prediction, but we wanted to learn more. Collecting statistics of what use cases are in the AI backlog. Simplify and focus our offering by which we encourage software engineers to start to use the Predictive Database.

Before the event I assumed we would get a colourful set of use cases from categorisation through product recommendations to demand forecasting. So we got, and most of the answers were pretty simple and clear automation or labelling stuff. A bit fancier like segmenting and meeting the demand of the target segments also occurred.

Antti, co-founder and the father of combining ML and DB. Demoing the Project success prediction use case. Photo credit: Fiona Kaihari

One repeated answer surprised. It came mostly from the mouths of the Startups, not the bigger firms that have more experience with machine learning. Now afterwards I think of it, it is not that surprising and as a Finn I should have predicted it.

We were having a dinner with an investor before Slush and were joking about how many different ways one can come up to say that the strength of a Finn is honesty and straightforwardness. Because there is nothing else. Just that. Honesty. Having lived for several years in the Middle East and China, and working in a business environment of other cultures like USA, I can say that Finns are absolutely awesome on being very straightforward and honest. That is unique.

Part of the Aito team at Business Finland booth

I do not think anyone can avoid sensing the hype aroundAI. In every conference or event, all around the world. Throw a Finn to that soup and you get honest and simple questions on what they do not understand. We want to look beyond the hype and challenge it and ask what's in it. We demand concrete evidence of what can be achieved. Concrete functional cases that are useful and bring value.

While I am writing this, the Posti (Finnish National post) strike is ongoing. On the news, one of the leading political influencer just said that in Finland the strength in negotiating has been a culture of trust where one can disagree openly. Despite disagreements, trust remains and contracts can be trusted. The above has already become a fundamental strength of the Finnish ecosystem of public and private sector.

See through the hype and ask the right questions

The Verge media network revealed a study that 40% of the startups in Europe who claims to offer AI, don't actually have it. Of course by now we know that it is unlikely that any Finn would describe her company in such a wrong way even if it might make sense to put a bit of colour to the marketing story. The 40% figure is sad, but understandable if people are not honest to themselves asking the most relevant question.

The answer that came up when we asked about what the extra machine learning engineer would be assigned to? It was "I would ask what useful can be done with our data and machine learning”.

No hype, no pöhinä, no made up use cases to outshine others on the brilliant knowledge. Down to earth honest and simple question. Exactly the right question the company in the journey of true AI adoption is constantly asking to find the best ways to create business impact.

We as the future builders of AI ecosystem need to help find the answer. Get away from fluttering for no particular purpose (the official definition of Pöhinä). It is irrelevant what AI you are being offered as part of the hype. Unless startups and other companies are equipped with the knowledge and skills to identify how to make business impact with machine learning, it is unnecessary to sell in cases where they will fail and in worst case lose major part of their R&D investment.

There are 2,5 Million data scientists in the world. I have not seen studies of how many of these are working in small and mid-sized companies and how many in larger enterprises. My empirical studies and gut feeling tells that most are acquired by those who already have power to do AI innovations. There are 25 Million software engineers in the world. Plenty working in SMEs. We should empower them with pragmatic, nimble and affordable tools that will help them speed up the AI adoption.

We will continue relentlessly to spark simple ideas about how to make business impact by offering Predictive Database and use cases we have done with customers. Building examples and instructions. Explaining the logic behind them. So that more people are equipped with understanding what is possible.

The power of machine learning belongs to every company. And understanding it’s opportunities is equally important.

Vesku

Aito means authentic, real, genuine, real, true. Just like I as a co-founder of Aito am. Proudly simple.

We also simply and honestly can have fun and not get too overwhelmed by the Startup life. Aito Predictive Database rocket launching at afterparty.