On a Mission to Democratize AI
AI is changing the world.
It’s changing the way we work, and the way we live.
AI offers the promise of a better future.
AI is exciting, and it’s attractive to companies around the globe, to technologists and to new talent alike.
But AI has a problem: the opportunities it creates are not evenly distributed.
Only a handful of universities offer AI courses, even in the US.
Information targeted at the general public is critically missing.
Many of the AI products currently on the market are severely biased against women and minorities.
AI has the potential of making work easier and safer for us all, but it is unfortunately putting people who struggle the most out of a job, and society leaves those people behind without retraining them.
And because AI is so incredibly expensive that only a handful of companies can truly participate in the AI race. This means that unless they work for one of those organizations, the most talented ML experts have no hope of building the generation of world-changing AI applications.
At Alectio, we believe a huge part of the problem comes from Big Data, and the misguided belief that without Big Data, one cannot train a high-performance model. Find a way to train those same models with significantly less data, and you give everyone a fair chance to benefit from the promises of AI.
We believe that we can democratize AI and change how it will impact society by changing the relationship the ML community has with Big Data. And we will make AI fairer, one dataset at a time.
– Dr. Jennifer Prendki, Founder and CEO, Alectio
We believe in “AI for All”.
The future belongs to all of us, not just a few privileged ones.
If AI is our future, we need to ensure that everyone benefits from the opportunities it creates, and that anyone can contribute if they want to do so, regardless of who they are and where they live. It means providing opportunities for anyone to learn about AI, and to study to become an AI expert if they want to.
It also means small and medium-size businesses should be able to leverage AI to grow and to build AI products to compete with the offerings of larger companies. This is only achievable if doing AI becomes more accessible and affordable.
Discover how Alectio strives to make AI accessible to All.
The first is through our Labeling Provider Marketplace, which helps small and medium-size labeling companies find customers and advertise their work. All labeling partners on our platform have their own social mission: some employ people with special needs, others focus on the disadvantaged communities that they serve. We also provide them with data-driven, customized feedback through our Labeling Partner Portal which allows them to provide the proper training to their employees and increase their earning potential.
The second way is through our fight against the myth that Big Data is king in Machine Learning; we jokingly call ourselves the “Data Slayers”, which is also the name of our online community. Our B2B platform empowers companies of all sizes to reduce the amount of data that they use to train models, dramatically improving their margins. Meanwhile, the community version of the platform serves two purposes: on the one hand, it helps propagate the message that building high-performance models with less data is possible (in fact, Data Curation often helps get better results), and it educates the next generation of ML scientists on how to select data efficiently – both relying on friendly competitions through which participants can earn swag, free ML books and online courses.
We believe in “AI for Good”.
Like all world-changing technologies, AI can benefit society… or be its downfall. AI for Good implies advancing AI Ethics at the same pace as AI Research. Hence, it means building AI responsible, and working on protecting ML models against bias simply isn’t enough. And it also means that building AI shouldn’t come at the expense of people’s privacy and peace of mind.
Discover how Alectio contributes to the "AI for Good" mission.
At Alectio, we strive to provide solutions that not only protects our customer’s privacy, but actually increases it. That’s why we decided to use an approach inspired by Federated Learning when developing our SDK to let our users benefit from our Data Curation technology without exposing their model or their data. Even better: by curating their data, our users eventually need to expose only fractions of their datasets to third-party companies or can avoid third-parties altogether when the compression is high enough that they can annotate data internally, preserving their and their customers’ data privacy.
At Alectio, we think about this constantly. Our goal is to dramatically reduce the amount of data you need for your machine learning projects so that AI is more accessible, less expensive, and more environmentally sustainable. We work with ethical labeling partners who care about their employees as much as they care about the quality of their work.
Responsible AI is another important topic for our team. We’re constantly thinking about ways to leverage our technology as an explainability tool, to provide transparency regarding the data records that caused a specific behavior in the model. While traditional explainability frameworks can only provide a reason why the model made a specific decision (i.e., a person is denied a loan because of their zip code), ours can state which records taught the model to flag people based on the location where they live, giving an opportunity to data scientists to correct biases instead of just identifying them. We have A major breakthrough in our research was the discovery that because most facial recognition models struggle to interpret the faces of dark-skinned people due to the difficult to identify shadows, a fair facial recognition algorithm would require a training dataset with more dark-skinned faces than white ones, challenging the traditional beliefs that classes should be fully balanced.
We believe in sustainable AI.
The fact that some Machine Learning models (in particular, Deep Learning models) are so data-greedy is not just bad news in terms of training time, and data labeling: it also means that they require an astronomical amount of computational power. Training state-of-the-art models in Computer Vision and Natural Language Processing can nowadays release a mind-boggling 600,000 pounds of carbon dioxide into our atmosphere, and require 300,000 times the compute resources they did less than a decade ago.
And with 2.5% of all carbon emissions coming from data centers nowadays, the Data Industry is literally the only one not actively trying to reduce its impact on the environment. Furthermore, with the ongoing race to ever larger models (think that some large companies have already developed models with 1 trillion parameters!), it’s easy to see how that number isn’t going to drop anytime soon, unless we make an effort as an industry to make our operations more environmentally friendly.
Learn how Alectio makes AI more sustainable.
Alectio’s core technology is based on reducing the amount of data needed to train a Machine Learning model. It means that with this technology, data scientists won’t just spend less time and money training models, but will also reduce their carbon footprint. That certainly won’t be enough to save the planet, but it is a very important step in the right direction.
Synthetic Data Generation is another topic that gives us concern at Alectio. We believe in its positive impact on AI research, but the Generative Adversarial Networks (a.k.a, GANs) used to generate data are among the most energy-inefficient models. In order to overcome this, we are adapting our curation technology to guide a synthetic data generation process into generating data strategically, so that less data needs to be created to reach similar results.
That being said, we know that companies will keep working with natural data for years to come, and had to make a difference there, too. Today, we’re moving the needle there by helping companies, in particular in the autonomous vehicles space, develop smart data collection strategies to avoid driving aimlessly in circumstances where informative data is sparse.
Machine Learning is for All of Us.
Regardless of whether you are an ML expert or not, Machine Learning is your ally. We believe in the power of Machine Learning, and that everyone deserves to learn about it and to benefit from it.
Unfortunately, Machine Learning and its societal implications are poorly understood in the general public. And we want to do our part in solving that.
That’s why we are investing into our online community, and are releasing the Alectio Community Platform designed to help anyone learn about Machine Learning and Data Curation. In particular, by challenging their friends and participating against the world’s best experts.
That’s also why we spend so much time writing, filming, and speaking about the subject, in a way that’s understandable by all regardless of their level of expertise on the topic. Therefore, we are constantly releasing new content in the form of webinars, blog posts and educational videos. So, if you want to learn more about Machine Learning, Data-Centric AI and MLOps, follow us on social media and/or subscribe to our newsletter. We cannot wait to grow together with you.
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