The Sequence Scope: Go Big First, Then Compress

Weekly newsletter with over 80,000 subscribers that discusses impactful ML research papers, cool tech releases, the money in AI, and real-life implementations.

📝 Editorial: Go Big First, Then Compress

Bigger models are better tells us the conventional wisdom in machine learning(ML). In the current state of the ML ecosystem dominated by supervised learning models, the mantra is to go big. Bigger deep learning models tend to outperform smaller versions in most deep learning scenarios. However, bigger models are also slow, expensive to run and really difficult to operate. Model compression is one of the techniques that helps address those limitations. As it names indicates, model compression tries to reduce the size of a given model without drastically sacrificing its performance.

🗓 Next week in TheSequence Edge:

Edge#75: the concept of N-Shot Learning; how OpenAI uses N-Shot Learning to teach AI agents to play; Learn2learn open-source meta-learning framework.

🔎 ML Research

More Efficient Transformers

🤖 Cool AI Tech Releases

GPT-3 Apps

💸 Money in AI

  • Construction monitoring startup Avvir raised $10 million in a funding round. The company uses laser scans and AI to catch construction mistakes, automatically update client’s building information modeling, and monitor construction progress.
  • Supply chain visibility platform FourKites raised $100 million in series D financing. FourKites uses data science to improve supply chain performance by predicting estimated time to arrival.
  • Risk management platform Feedzai raised $200 million in Series D round. Their goal is to fight financial crime by leveraging big data and advanced ML.
  • Translation service Language I/O raised $5 million in A round funding. Their AI technology allows generating accurate, company-specific translations of all user-generated content (UGC) including jargon, slang, abbreviations and misspellings into over 100 languages via chat, email, article and social support channels.
  • Dataminr raised $475 million in new funding. Dataminr’s real-time AI platform detects the earliest signals of high-impact events and emerging risks from within a mix of 100,000 public data sources.
  • Edge AI startup LGN raised $2 million in funding. Their solutions allow edge AI systems to operate resiliently, in the real world, at scale. Delivering edge AI at scale is the first step in LGN’s mission to create networked AI, meaning AI-to-AI communication, without human in between, element, to speed up the decision-making and action processes.
  • AI-powered marketing optimization platform Sellforte raised $4.78 million in funding. Their data science models calculate comparable ROI for every marketing investment across different media channels and campaigns, generating continuous recommendations for growth.
  • Identity verification startup Jumio raised $150 million in a funding round. Leveraging AI, biometrics, machine learning, liveness detection and automation, Jumio helps organizations fight fraud and financial crime, onboard good customers faster and meet regulatory compliance including KYC, AML and GDPR.
  • Workflow and decision automation startup Camunda raised $100 million in a Series B round. The company offers process automation with a developer-friendly approach that is standards-based, highly scalable and collaborative for business and IT.

CEO of IntoTheBlock, Chief Scientist at Invector Labs, I write The Sequence Newsletter, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

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