Not all data is created equal
You can build better models with less data. We can show you how.
The only data curation and machine learning optimization platform you’ll ever need
While Big Data helped usher in widespread adoption of AI, it’s also responsible for its high price tag. After all, storing all that data is a real expense. Labeling it is onerous. Training models on those gigantic datasets is costly and time-consuming. And in business, “slow and expensive” is rarely a recipe for success.
Thankfully, the solution lies inside the Big Data you already have: it’s data curation. It’s Smart Data instead of Big Data.
Alectio’s platform uncovers this smart data. It’s like a wrapper that sits around your existing models and “listens” while it trains. It understands what data is actually helping your model—and what data is hurting it.
Why we created Alectio and how it works:
Big Data vs. Smart Data
The most pervasive misconception in data science is “the more data, the better.” This idea that getting more and more data will make models more accurate or that collecting more data can magically fix struggling models.
That’s simply not true.
The reality is that in any given training data set, only a fraction of it is generally useful. The rest is useless (redundant information, for example) or actively harmful (like data from faulty sensors or poorly labeled rows from your labeling provider).
Alectio is made to help you find the right data to train your models on. No matter what kind of data you’re working with, be it images, text, video, or audio, we can help. Alectio is data and model agnostic. In fact we don’t even need to see your data or your model.
In the world of machine learning, Goliath is Big Data. If you want to enlist your own David to fight back, we’re here to help.
Why less is more
MORE DATA MEANS LONGER TIME TO MARKET
Data scientists spend up to 80% of their time preparing training data. More data means longer training times and reduced or delayed ROI.
DATA IS EXPENSIVE TO PREPARE AND PROCESS
Data processing isn’t cheap. Servers, data warehousing, and data labeling add up quickly. Relying on hardware-centric solutions just isn’t feasible long term.
BAD DATA IS THE ROOT CAUSE FOR MODEL UNDERPERFORMANCE
It doesn’t matter how good your models are if you’re training them on bad data. As datasets balloon in size, it’s often difficult to uncover what’s hurting performance.
Get Started For Free
You can download Alectio and start experimenting on your own by clicking the button below. If you’d like to get in touch to learn more, just email info@alectio.com or click the “Contact Us” button in our nav bar and we’ll get back to you.
Our latest blogs and resources:
Leveraging Active Learning on Small Datasets
At Alectio, we’re usually known to help ML teams reduce the size of their datasets; our typical users come to us when they have more data than they know what to do with, and when training on their entire dataset is just not feasible, the reason being that most people...
Planes, Training and Anomalies (or How Much Data is Really Needed When Working with Sensor Data?)
If you are an avid Alectio follower, you’ll know by now that efficient training is what we do. It is not just a matter of philosophy (even though it is, as we have described here, here and here); it’s also a simple matter of economics. For many companies in a wide...
9 Reasons Why Active Learning is Not Widely Adopted
The Machine Learning field is full of buzz: deep learning, LSTMs, generative adversarial networks; the list keeps going on and on and on. Some of the most promising concepts, though, stand at the other end of the spectrum. Active learning has to be one of the top...