Artificial intelligence holds the power to revolutionize business performance and operations, but most AI solutions are limited by one very simple – but important – factor.
They don’t know what they don’t know.
95% of the world’s AI solutions have been built using a common set of frameworks – such as neural networks and collaborative filtering – that were developed to make AI accessible and easy to use.
While these solutions have powerful applications, they can only form predictions based on behaviors that match patterns in data they’ve previously ingested. Because of this, they require massive amounts of data to train themselves for every possible scenario they might encounter.
In short, what goes in determines what comes out.
This is why the vast majority of AI solutions are purpose-built for specific use cases. Take chess for example. With traditional AI solutions, it’s easier to train a chess AI model by supplying it with data on every possible chess move that’s ever been used in the past. But, in doing so, the resulting AI technology is only useful when applied to chess.
Unfortunately, human behavior is unpredictable, and past behavior is a poor predictor of future actions.
This is where the majority of AI tools fail to deliver value.
- They can’t even begin to function until they’ve ingested huge amounts of data.
- They are good at learning, but not at “unlearning.”
- They are incapable of solving for chaos in limited data.
- They bucket users into groups based on their similarity to past users and make assumptions about them – assumptions that are not always correct.
Proto AI’s proprietary Seraphim Predictive Science™ technology has reimagined the way artificial intelligence works by relying on real time behavior, rather than vast troves of historic data, to make predictions.
Unlike traditional AI, Proto AI’s next generation AI:
- Makes it possible to understand what will happen in the future – and make decisions based on that understanding – without ever having seen something similar in the past.
- Delivers results – and value – right away because it does not require vast amounts of historic data in order to function.
- Is flexible, and can solve for use cases that it has not specifically been trained for.
- Can quickly learn things, and just as quickly “unlearn” to deliver better, more accurate results.
- Looks at individual behavior patterns and enriches it with contextual signals and data gathered from advanced data sampling and inference to quickly get smarter and deliver custom recommendations.
What does this look like in practical terms?
In that chess example, even if Proto AI hasn’t seen a particular chess move in the past, it could still predict that it should happen based on the moves it sees players making in real time.
While chess games are a simple way to illustrate the power of AI, we’re not in the business of solving for chess moves.
We ARE in the business of helping other businesses accelerate performance, drive efficiency, grow profitably, and outpace the competition.
One of the first areas we’ve applied Proto AI is in ecommerce.
Today’s ecommerce businesses have massive opportunities, but are struggling to take advantage of them due to unprecedented challenges and complexity relating to rising customer acquisition costs, supply chain interruptions and excess inventory.
Profitable growth in ecommerce requires maximizing average cart value while moving inventory across all product categories – not just the most popular ones.
Proto AI is empowering ecommerce retailers to tackle these challenges with AI-powered product recommendations that deliver highly personalized customer journeys.
Most AI and product recommendation engines offer alternatives to something users are already looking at – for example, a green tent rather than a blue one. They are also trained to recommend the most popular “best sellers,” based on items that similar users have purchased in the past, which tends to result in excess inventory for things that don’t make that list.
By contrast, Proto AI solves for the individual user by recommending items that compliment what that user is looking at – such as hiking boots for a user who is looking at a tent – whether those items are best sellers or not.
The result is a better experience for customers, leading them to spend more and purchase more items, and better results for retailers who experience higher conversion rates, stronger sales growth, and less inventory spoilage.
Best of all, Proto AI requires very little data to function, making it easy for companies large or small to get started quickly and see value in days, not months.
Proto AI is different by design, and we’re on a mission to reshape the way businesses operate with next generation tools and solutions that help them make better, smarter decisions, faster.