The alwaysAI Blog

alwaysAI now open to meet growing demand from computer vision developers

Easy-to-use development platform brings together pre-trained computer vision models, innovative APIs, starter applications and edge environments

Finding the Right Model with the New alwaysAI Model Catalog

With the new alwaysAI model catalog, you can now search for a computer vision model by specific criteria; for instance, you can search by label to ensure that the model includes a label for the type of entity that your application needs to be able to recognize. You can also search for a model that is compatible with the kind of service that you want your application to provide (object detection, image classification, or pose estimation), and then further refine your search with filters for...

alwaysAI Experiences Rapid Growth Following Series A Funding

alwaysAI, a developer platform that fast-tracks the creation and deployment of computer vision apps on edge devices, today announced significant momentum following the close of its Series A funding earlier this year.  In addition to adding more than 500 developers to its beta program and expanding its corporate team, alwaysAI also formed two new partnerships for rapid computer vision prototype development and deepened its relationships with NVIDIA and Qualcomm Technologies, Inc.

Upcoming Events: Autumn 2019

Want to speak with us about opportunities for your business to accelerate Deep Learning Computer Vision on the edge?  Interested in a demo of the alwaysAI platform? Our team will be at AI events in September, October and November 2019 in California, and we're open for conversations.

alwaysAI Appoints Scott Miller as Head of Product and Partner Management

alwaysAI deepened its management bench today with the appointment of Scott Miller as Head of Product and Partner Management.

alwaysAI Joins NVIDIA Inception Program

alwaysAI today announced it has joined the NVIDIA Inception program, which is designed to nurture startups revolutionizing industries with advancements in AI and data sciences.

Former Blackberry COO Founds AI Company in San Diego

Two experienced tech executives moved to San Diego to create a company that would make it easier for developers to use AI technologies. Former Blackberry COO Marty Beard and former Sphera Solutions CTO Steve Griset founded AlwaysAI in Solana Beach last May, picking the San Diego area for its expertise in big data, neuroscience and mobile technology.

Term Sheet - Tuesday, January 15

While we’re all obsessing over Bitcoin’s price fluctuations, blockchain technology keeps advancing in its shadows. At least that’s what the CEO of newly-launched cryptocurrency venture Bakkt thinks.

Computer Vision Startup Takes $4M in Series-A Funding Round

“The platform’s tools will allow for the development of computer vision systems that can detect, classify, count, and track objects, and that can perform facial recognition.”

alwaysAI announces $4M Series A Funding from BlueRun Ventures

alwaysAI today announced the close of a $4M Series A funding round to bring its deep learning computer vision (CV) platform for embedded devices to enterprise developers. The funding was led by BRV, a leading Silicon Valley venture capital firm, with participation from co-founder and CEO Marty Beard. alwaysAI will use its funding to broaden and commercialize its deep learning CV platform and expand its team.

alwaysAI Raises $4M in Series A Funding

alwaysAI, a San Diego, CA-based provider of deep learning computer vision (CV) platform for embedded devices, closed a $4M Series A funding round.

California AI startup gets $4 million in funding from BlueRun Ventures

The San Diego-based artificial intelligence startup alwaysAI has announced a $4 million Series A funding round backed by BlueRun Ventures. The company announced that this latest investment will bring its deep learning computer vision (CV) platform to developers.

AlwaysAI Adds $4M to Bring Deep Learning to Embedded ‘Edge’ Devices

Many of our devices, from wearables to medical instruments to drones, can capture reams of images. Using algorithms to analyze those images on the devices, in turn, generally takes loads of computing power and energy—sometimes more than is feasible.