Edward Turner of TMR Blog recently covered our work on COVID-19. He did a nice job summarizing the potential efficacy of our algorithm in an understandable and digestible manner, while including EVQLV’s optimism on the project.
EVQLV Media
How Structurally Similar is SARS-CoV-2 to SARS?
Brett Averso (CTO, EVQLV) shows and explains the undeniable structural similarities between SARS-CoV-2 and SARS. We hope this video serves to dispel some of the myths you may have encountered during your search for answers surrounding coronavirus.
EVQLV Featured in insideBIGDATA
Our work with ImmunoPrecise on COVID-19 was covered by insideBIGDATA. They did a fantastic job covering the piece originally published by Columbia Data Science Institute, highlighting a few fantastic quotes
EVQLV Submits First Panel of Optimized Antibody Sequences
EVQLV, has submitted their first panel of candidate therapeutic antibody sequences, comprised of DNA sequences encoding for potentially therapeutic antibodies against the new coronavirus, SARS-CoV-2. These DNA sequences were generated using computational antibody design, a method which combines mathematics, statistics, and computer science to identify high-affinity antibodies.
5 AI Companies Using Epidemiology to Fight Coronavirus
In the AI vs COVID-19 battle there are three major areas where breakthroughs are needed, coming and have arrived: diagnosis, treatment and epidemiology. In this post, we focus on five companies who are using epidemiology to aid researchers and the general public in the fight against COVID-19.
Cross-Reactivity between SARS Antibodies and SARS-CoV-2
The SARS antibodies are not cross-reactive with SARS-Cov-2. However, we can potentially use artificial intelligence to design variants of the existing SARS antibodies which are cross-reactive with SARS-CoV-2.
Coronavirus Visualized
Brett Averso, CTO, and I recently had a follow up discussion on our first coronavirus chat. Brett provided visualizations and commentary on coronavirus (SARS-CoV-2), ACE2, SARS-CoV-2 with SARS overlay, and antibody fragments to help people better understand the threat we’re currently facing, as well as put it in its proper context. Brett also discussed the role AI can play in finding an effective treatment for COVID-19.
DSI Alumni Use Machine Learning to Discover Coronavirus Treatments
Columbia Data Science Institute recently covered EVQLV’s work towards developing therapeutic candidates against COVID-19 with Immunoprecise Antibodies.
The 4 Stages of Learning
The 4 stages are fairly simple: luck, avoiding failure, learning from failure, learning from success. The biggest takeaway is the importance of the 4th stage. It’s far too common for us to achieve a desired outcome and never evaluate how we could have improved our performance.
A Discussion on the Coronavirus (SARS-COV-2)
Brett Averso, CTO, and I linked up to discuss the coronavirus (SARS-CoV-2). Brett covered what exactly the coronavirus is, the threat it currently presents, how we can best protect ourselves and our loved ones against infection, and what EVQLV is doing to address the outbreak.
Can AI make us more human?
Legitimate concerns notwithstanding, Andrew Satz and I recently discussed how EVQLV understands and utilizes AI. During the discussion, Andrew proposed the idea that far from stripping us of our humanity, AI may allow us to become more human.
How does EVQLV understand and utilize AI?
AI or artificial intelligence is a term that gets thrown around constantly in the tech space. In our most recent discussion, Andrew Satz (CEO, EVQLV), covers what it means when a company says they’re leveraging AI, how EVQLV is utilizing AI, the different types of AI (hint: that “A” doesn’t always mean artificial), and perhaps most interestedly, how AI can make us more human.