Excited to share what we've been building at Synthefy, the world's first #multimodal generative AI model for #timeseries data.

Curious about the value proposition of #DecentralizedAI? Let's go over a popular project #bittensor and describe why it’s crucial to have external demand and real utility for AI services.

Excited that we've been selected in the top 12 companies worldwide for the Deutsche Telekom and T-Mobile AI in Telecom Challenge 2024

Excited that we've won Deutsche Telekom and T-Mobile 's AI in Telecom Challenge for a first place prize of 150K Euros! Reach out to see how our multi-modal time series platform can help your business. Press release here: telekom-challenge.com/interview-with… Shubhankar Agarwal Sai Shankar Narasimhan anand iyer

Excited to share our new paper in ICML Conference on #synthetic time series generation using #diffusion models!

We will be at ICML Conference presenting our spotlight work - TimeWeaver, a GenAI model for multi-modal time series synthesis! Come meet the Synthefy team to chat at Poster #316 (Hall C 4-9 #316) on Thursday. Would love to show what we are working on. Sandeep Chinchali anand iyer Sai Shankar Narasimhan

Ever wondered how synthetic time series data can be a game changer? 🧐 Our latest blog breaks it down with real-world examples. Dive in and tell us how you will use synthetic time series data! medium.com/@synthefy/prac…

Agentic platforms like Synthefy are enabling companies, like Dell, to go from pure observability to predictive maintenance. Pre-LLM era of ops involved humans managing and monitoring multiple dashboards, while trying to coalesce multiple sources of data to identify the source

LLMs are amazing at a lot of things - but time series forecasting isn’t one of them. In Synthefy's latest blog post, we explain why token-based architectures aren’t inherently designed for real-world time series tasks - like forecasting energy demand, retail trends, or medical

Imagine asking: 📦 “Forecast delivery demand if I cut shipping fees in half this holiday season.” 🛋️ "Forecast my couch and tables, if I start promoting couches over tables this labor day" …and getting answers in minutes, not months. No messy data pipelines. No Model

Positive transfer is one of the key concepts that unlocked foundation models. If you train a model on math, physics, Shakespeare, and coding together, it gets better on each dataset than a model trained on a single task or dataset. Why? Because there is positive transfer —

For the past few years, our fund Canonical has been laser-focused on "Decentralized Intelligence." During our AGM last week, I presented our investment thesis and why we are excited about backing founders building in this category. We want this work in the open, so we are