Companies differentiate themselves with both their products and their ability to collect data and glean insights. Machine learning powers AI capabilities like recommendation systems and predictions. From increasing user satisfaction with personalized content to reducing costs with automation, machine learning leverages data science and modern data processing to make predictions and emulate human decision-making. AE offers a unique blend of development expertise, domain knowledge, and quantitative savvy.
At AE, our mission is to improve human agency with every client, every line of code, and every machine learning model we assemble.
AI teaches computers to recognize patterns that challenge humans at scale (can you remember what was similar and different across 100 attributes of 1,000,000 things?). AE helps businesses sort through the multitudes of things (customers, images, SKUs, transactions, etc.) and extract the insights that lead to value!
A picture is worth a thousand words, but at AE, we’d prefer to measure its value in dollars. Computer Vision allows not only the classification of cat memes but also patterns in data visualizations. What other pictures are alike? Are certain pictures preferable or profitable? We see what others don’t (or, you know, write code to do it for us).
George Carlin said that “your words always give you away,” and although he might have been considering a particular “seven”, they’re still a treasure trove of insight. What do customers say about products? What sentiments are revealed by discussion? Is a person interested in buying X if they say Y? Let our algorithms read, report & add value!
Which customers will increase their spending? Meeting the desires of tomorrow’s consumer (maximizing their agency) requires optimizing the supply chain today. Determining the lifetime value of any asset demands mathematics to peer forward in time. The view is hazy, but value lives in that fog.
Folks willing to read this dubiously witty passage also found other prose on our website compelling (yay!). One revealed preference can reveal others. At AE we get to know what our clients and customers want—and such insights reveal ROI.
Time is money. And nothing wastes more time than repetition (and repetition). Increasing human agency means freeing up time for you to do what you do best (thinking, innovating, and watching tv) and letting computers work the long hours (they don’t even get paid overtime or receive workman’s comp. Suckers.)!
Humanity’s greatest cognitive gift is the ability to recognize patterns. Our greatest limitations are speed and memory. We can’t look at, nor remember, all the things (much to the chagrin of colleagues and significant others). Human agency is maximized when our feeble brains are amplified by modern computing (even if it means a few extra cat videos and memes along the way)!
A “Brain-Computer-Interface” (BCI) sounds fit for the Starship Enterprise. But neuroscientists are already developing tools to monitor the brain’s responses to auditory and visual stimuli. Human agency means maximizing the potential of our cognition. We channel revenue generated from client projects and internal skunkworks, in part, towards collaborations with researchers at CalTech and beyond. Machine learning tools should enhance the fluency and ease with which human beings communicate and thrive.
The question is not whether such technology will be developed. The question is by whom and for what purpose. AE aspires to ensure that BCIs increase the agency of humanity (and perhaps other species!).
NLB aims to regularly organize benchmark suites, a collection of tasks, datasets, and metrics around a theme in neural latent variable modeling. The competition featured five primary datasets on which teams' models were tested. Each model was deployed on neural data in different regions of a monkey's brain from electrode arrays implanted in the motor cortex.
We are thrilled to come out victorious in the first phase of neural latents benchmark challenge (NLB), topping the leaderboard in every category! We reinvested the prize money to sponsor a successful phase II of NLB Challenge and offered cloud computing grants to participating teams. This is the first step on a long journey, and every participant will play a part.
We believe in making data maximally useful to benefit society and increase human agency. We believe that privacy should be central to that consideration. Technology designed to empower users, corrupted by the wrong financial incentives, can ultimately diminish their agency. At AE, we are focused on researching and developing best privacy practices for unlocking the potential of your private data on your terms. Read more about our Privacy Preserving Machine Learning services.
Building great models is only the first step. Deploying models efficiently and monitoring their performance is crucial to a successful ML project. Once deployed, models must be continuously monitored to ensure they are delivering accurate and reliable results. This requires experienced engineers who can both identify potential issues and understand the underlying business well enough to make the necessary adjustments to keep your models (and enterprise) running smoothly.
Karl Pearson (the guy who developed the correlation coefficient we call ‘rho’) said ‘That which is measured, improves’. Don't leave your model deployment and monitoring to chance - it's essential to have a team of experts on your side.
Want to talk about machine learning or simply learn more about AE?
We help our clients solve fascinating problems (and solve interesting ones of our own!).
Our bodies are full of medically-relevant insights. A trip to the doctor’s office to urinate in a cup is unpleasant and expensive. What if you could urinate on a stick, take a picture with a smartphone, and access a plethora of health and wellness insights? Yup. Better.
AE built a computer vision algorithm to scan that stick. The algorithm improved 190% over the existing system, Vessel raised additional financing, and human beings everywhere (5k pre-orders already!) will soon gain insights into their bodies from the comfort of their bathrooms.
Humans exercise for many reasons—some want to get stronger and faster, others simply want to look good (no judgment). With all manner of wearable technology upon our bodies, shouldn’t that data inform when, how, and for how long we exert ourselves? Shouldn’t human agency include improving our motivation and gaining insight into the progress each workout delivers? (Says the guy who’s been sitting at a desk all day.)
AE helped Point conceive and develop their SDK, model the data it receives and creates, and generate actionable health advice for health platforms and users. Platforms that use the Point SDK can now get effortless data on their users effortlessly, which enables those users to exercise efficiently, wisely, and with maximum agency to achieve their personal goals.
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