Data to AI Lab at the Laboratory for Information and Decision Systems
Cambridge, MA
Joined June 2018
- Tweets73
- Following54
- Followers306
- Likes25
MIT - Data to AI Lab retweeted
Excellent article in @Forbes today calling #syntheticdata “an all-too-rare example of…genuinely useful” generative AI, for the particular application of software testing.
Read @jpwarren profile of @datacebo and @kveeramac :
forbes.com/sites/justinwarre…
#bigdata #syntheticdata #generativeai #data #datascience #enterprisedata #tabulardata #predictiveAI #machinelearning #ML #generativemodels #MLmodels #productiontesting #softwaretesting #cybersecurity #hacking #infosec #security
MIT - Data to AI Lab retweeted
Young scientists regularly ask me for career advice. Academia or industry? Big company or startup? US or Europe? Good scientists in AI disciplines are fortunate to have many choices. But choosing can be stressful. I always give the same advice. 1/10
Great article from @thenewstack about open source to business highlighting @datacebo a spin out from DAI lab.
What’s Next for Companies Built on Open Source? thenewstack.io/whats-next-fo… @ha_joslyn #OpenSource #KubeCon #CloudNativeCon
Congratulations @XuLeonard for having his paper on generating #syntheticdata using conditional GAN 1000 citations!
Really excited to announce that our NeurIPS 2019 paper on 'Modeling tabular data using conditional GAN' has surpassed 1k citations! It's inspiring to see researchers applying the model innovatively in the era of LLMs. #NeurIPS #GAN #SyntheticData #MIT
MIT - Data to AI Lab retweeted
Startup Spotlight: @DataCebo: clouddon.ai/startup-spotligh… < checkout my post & video interview with @kveeramac to learn more about how DataCebo uses GenAI to generate high quality data at scale.
#SyntheticData #GenAI
MIT - Data to AI Lab retweeted
CTGAN is a collection of #deeplearning #syntheticdata generators developed at MIT's @lab_dai and one of the most popular models in our #opensource SDV library. Read the what, why & how here 👉ow.ly/E6sy50MOHej #machinelearning
There is a reproducibility crisis in #healthcareAI — but it's not about #datasharing or #privacy. Here are some key learnings we found when developing a structured model-building process with automated tools 👉 ow.ly/jqiT50MHkzG #autoML #machinelearning #automation
We had much to #celebrate in 2022: Alicia Sun (PhD SES) & Lei Xu (PhD EECS) (both toasting in top left image) successfully defended their doctoral theses. AND we were finally able to celebrate Micah Smith (PhD CS)’s 2021 @MIT graduation in person w/ @kveeramac #PhDCelebration
Part of our mission is to identify #ML usability challenges. End-user comprehension is a major one. So we’ve developed a taxonomy to craft features non-#AI experts can understand & become more comfortable using #machinelearningmodel outputs. ow.ly/YRLn50Mw7g2 #ExplainableAI
#Diversity, #equity, #inclusion AND #machinelearning! Way to go @MIT_SCC for encouraging the next generation of #ai pioneers. news.mit.edu/2023/break-thro…
What’s in store for #AI in 2023? The #OpenSource revolution where startups and academia could (and should!) become the epicenters for fundamental AI research, no longer beholden to #BigTech. technologyreview.com/2022/12…
Read the @VentureBeat article explaining our recently published research on creating high-quality sentences using #LLMs to train better robust #machinelearning models for language tasks.
👉 venturebeat.com/ai/how-mit-i…
Read our research paper here 👉 aclanthology.org/2022.findin…
🥳Our very own #MIT Data-to-AI Lab alum Zara Perumal has just been named to the 2023 @Forbes #30under30 for #EnterpriseTechnology. Congrats, Zara! 🎉🍾Looking forward to seeing what great things you'll accomplish in 2023! 💫🚀 ow.ly/u6ji50LRjmp
It’s not always about data science & algorithms...But it’s always about camaraderie & collaboration.
Last week, over bowling & drinks, @kveeramac and the @lab_dai team bid farewell to Mihir Thalanki (2nd from right), who was visiting us from @bitspilaniindia.
#teamspirit #MIT
We made it! After a year and half of no outing. Thanks @AlexandraZytek for organizing the hike and leading the way. And welcome back to Boston @lab_dai alum @n4atki and Katharine Xiao.
MIT - Data to AI Lab retweeted
Great chatting with @MattGoodingTM about privacy and how synthetic data can help. Did not get a chance to go into details, but good to highlight that one should avoid broad statements - this is good for privacy, this is not…
“Access to data is the number one issue and the first problem we encounter in any [AI] project,” says @kveeramac. Is synthetic data the answer? buff.ly/3AFnnFg
MIT - Data to AI Lab retweeted
We love a good data science competition, but a winning, all-purpose ML model does not exist in the real world. Our users have taught us about trade-offs & we evolved to provide more choices. See our latest #syntheticdata article by @n4atki. bit.ly/feedback-models
