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Research#llm📝 BlogAnalyzed: Dec 24, 2025 08:19

InstaDeep's NTv3: A Leap in Multi-Species Genomics with 1Mb Context

Published:Dec 24, 2025 06:53
1 min read
MarkTechPost

Analysis

This article announces InstaDeep's Nucleotide Transformer v3 (NTv3), a significant advancement in genomics foundation models. The model's ability to handle 1Mb context lengths at single-nucleotide resolution and operate across multiple species addresses a critical need in genomic prediction and design. The unification of representation learning, functional track prediction, genome annotation, and controllable sequence generation into a single model is a notable achievement. However, the article lacks specific details about the model's architecture, training data, and performance benchmarks, making it difficult to fully assess its capabilities and potential impact. Further information on these aspects would strengthen the article's value.
Reference

“Nucleotide Transformer v3, or NTv3, is InstaDeep’s new multi species genomics foundation model for this setting.”

PermalinkMarkTechPost
Research#AI in Engineering📝 BlogAnalyzed: Dec 29, 2025 08:04

Automating Electronic Circuit Design with Deep RL w/ Karim Beguir - #365

Published:Apr 13, 2020 14:23
1 min read
Practical AI

Analysis

This article discusses InstaDeep's new platform, DeepPCB, which automates circuit board design using deep reinforcement learning. The conversation with Karim Beguir, Co-Founder and CEO of InstaDeep, covers the challenges of auto-routers, the definition of circuit board complexity, the differences between reinforcement learning in games versus this application, and their NeurIPS spotlight paper. The focus is on the practical application of AI in a specific engineering domain, highlighting the potential for automation and efficiency gains in electronic circuit design. The article suggests a shift towards AI-driven solutions in a traditionally manual process.
Reference

“The article doesn't contain a direct quote, but the discussion revolves around the challenges and solutions in automated circuit board design.”

PermalinkPractical AI
Research#AI in Logistics📝 BlogAnalyzed: Dec 29, 2025 08:10

Deep Reinforcement Learning for Logistics at InstaDeep with Karim Beguir - Episode Analysis

Published:Sep 25, 2019 12:54
1 min read
Practical AI

Analysis

This episode of Practical AI features Karim Beguir, CEO of InstaDeep, discussing the application of deep reinforcement learning (DRL) to solve complex logistical challenges. The conversation likely covers InstaDeep's approach to building decision-making systems, including data acquisition, the efficiency of RL compared to other methods, and the importance of explainability in their models. The focus is on practical applications of AI in a real-world business context, highlighting the challenges and opportunities of using DRL in logistics. The episode likely provides valuable insights into the process and mindset of a company at the forefront of AI development.
Reference

“Karim Beguir discusses logistical problems that require decision-making in complex environments using deep learning and reinforcement learning.”

PermalinkPractical AI