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macrozack (τ, τ) 🚀
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Builder @bitstarterai Director @MacrocosmosAI Editor @taotimesdotai Convening Bittensor's @ExploitSummit 🧩 chriszacharia.substack.com 🚀
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Latest posts 5
On the mic today 🎤 on stage with @willobrien, on message for Bittensor and SN87
AI agents need more than autonomy. They need evidence at every handoff, with people retaining control.
At @AIBC_World Rome, @willobrien joined @macrozack of @bitstarterAI to discuss governed autonomy and open access to compute, operations and capital.
#AI #Bittensor #SN87View quoted post on X
Wait, Synth's miners outperform Opus 5.5 - and GPT-6 Google Gemini
Against a live benchmark for agentic AI quant activity, over 30 days Synth won easily
Am I reading this right bittensor:native
Against a live benchmark for agentic AI quant activity, over 30 days Synth won easily
Am I reading this right bittensor:native
A live benchmark for AI-driven quant research.View quoted post on X
Challengers: @AnthropicAI’s Opus 5.5, @Google’s Gemini and @OpenAI’s GPT-6 Astra.
One briefly hit #1. None sustained a win over Synth’s best quants over 30 days.
Results, code, methodology:
github.com/synthdataco/au…
100% - if you haven’t come across @tensorlink_dev or his work on @cascade_sn91, you’re missing one of Bittensor’s best builders.
Post below explains how you can deploy our time series API as forecasting infrastructure, “saving weeks of guesswork.”
Post below explains how you can deploy our time series API as forecasting infrastructure, “saving weeks of guesswork.”
The Bittensor community is as strong as ever and gets stronger by the day.View quoted post on X
Along my journey I've found many great people and @tensorlink_dev from @cascade_sn91 is one of those great people.
Massive thanks to Chris he has saved us weeks of guesswork.
We run Cascade's synthetic time-series generator as a research substrate. The Alphacast feed sits alongside it as forecasting infrastructure. Both have become core pieces of our engineering stack.
Research-stage, and one live deployment which we constantly update,the capability jump has been huge. I can't go into to much detail but I can say this,without the Cascade tech we wouldn't really have an edge. Not only is the tech been built on SN91 brilliant it's highly versatile. It's like giving an acromat artist color vision which really broadens your horizons Cascade is a truly remarkable technology.
gScade🫡
Get the MCP: ephemeris.cascade.industries
Join the Telegram: t.me/cascade_sn91
SN91 is now training a 1B parameter model.
If 1B sounds small: the new model will rank among the largest time series foundation models, ever.
And our current model - with only 4M params - already beats Salesforce's 91M model.
Which means: we're going after SOTA.
If 1B sounds small: the new model will rank among the largest time series foundation models, ever.
And our current model - with only 4M params - already beats Salesforce's 91M model.
Which means: we're going after SOTA.
From 4M to 1B+. Cascade’s biggest upgrade yet.
We’re preparing to train Cascade-MoE: a mixture-of-experts time-series foundation model targeting 1B+ total parameters.
We’ve shown that synthetic data generated by Bittensor miners can train a 4M-parameter forecasting model from scratch, reaching parity with Toto 2.0 4M. Now we’re scaling up, with SOTA forecasting as our goal.
Cascade-MoE will use a learned router to select combinations of expert networks based on patterns in the input, alongside an always-active shared expert. This gives the model access to specialised capacity without activating every stored weight for every input.
We’re also evolving the competition so miners can generate synthetic data targeted at particular domains and time resolutions, such as hourly versus daily series.
The architecture is designed to support targeted training of selected expert subsets, while the subnet tests whether contributions improve forecasting performance.
The goal: SOTA forecasting accuracy, built through competition on #SN91.View quoted post on X
