Monday, 3 August 2026 Sign in

DataScience SG

Company ● Covered in 4 stories Compare ⇄ + Follow

This profile is built automatically from TLDRocket coverage.

Signals

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Media momentum

As of 3 Aug 2026 · Visible stories in the last 30 days, compared with the 30 days before.

1 source

Source diversity

As of 3 Aug 2026 · Distinct publications behind this entity's visible coverage.

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Release activity

As of 3 Aug 2026 · Model, product and open-source release events in the last 90 days whose coverage involves this entity.

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Funding signals

As of 3 Aug 2026 · Funding and acquisition events in the last 90 days whose coverage involves this entity.

Jun 2015 → Jan 2020

Coverage span

As of 3 Aug 2026 · First to most recent month of TLDRocket coverage of this entity.

Latest developments

DataScience SG Meetup - RecSys, Beyond the Baseline Eugene Yan · 6 years ago · 41

DataScience SG x ODSC Meetup - Applying ML to Healthcare Eugene Yan · 6 years ago · 6

DataScience SG Meetup - Panel On the Different Roles in Data Eugene Yan · 7 years ago · 19

DataScience SG Meetup - How we got top 3% in Kaggle Eugene Yan · 11 years ago · 30

Timeline

Month Quarter Year

January 2020

14 Jan DataScience SG Meetup - RecSys, Beyond the Baseline

October 2019

9 Oct DataScience SG x ODSC Meetup - Applying ML to Healthcare

January 2019

17 Jan DataScience SG Meetup - Panel On the Different Roles in Data

June 2015

20 Jun DataScience SG Meetup - How we got top 3% in Kaggle

The daily briefing

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TLDRocket 3 August 2026

The story of AI in August 2026 is one of consolidation meeting enforcement. Alibaba's Qwen3.8-Max, a 2.4-trillion-parameter mixture-of-experts model with a million-token context window, arrives as a direct challenge to OpenAI and Anthropic's frontier offerings—priced at $2 per million input tokens, it's positioning itself as the capable-and-cheaper alternative that China's AI push has long promised. But the more consequential development is structural: enterprises are finally getting the plumbing to actually deploy these models. June, backed by Salesforce's Marc Benioff, raised $20 million to automate AI integration into legacy systems, scanning corporate infrastructure and generating deployment workflows without expensive consultant fees. This solves what's become clear as the real bottleneck—not model capability, but implementation friction in messy, heterogeneous corporate environments.

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