For folks wondering why Series B specifically: Pre-seed is testing Seed is product-mkt fit
Series A is cost & model efficiency
Series B is scale
AI
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Series B Funding: Scaling Phase After Product-Market Fit
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Alteryx 2023.1 Release: Enterprise Cloud Analytics Platform
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ICYMI: As the year of the #AlteryxCloud, you can now look forward to our latest release: 2023.1. Enterprise-ready and cloud-friendly! Watch this overview video for more details on the enhanced capabilities now at your fingertips: https://
youtu.be/oBsZc3fIU90 #AnalyticsForAll -
Series B AI Startups Shift Focus to Enterprise Monetization Strategies
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Seeing more Series B AI startups without strong monetization have to double down on enterprise use cases like this and restructure their GTM teams. LLMs are too expensive to maintain both for free (unless you have $100M+ in funding).
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Women Leading Technology and Innovation in the Digital Era
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Women Leading Tech and #Innovation https://
bit.ly/3kZzvOx #WomeninTech #leadership -
OpenAI’s Losses Doubled to $540 Million Developing ChatGPT
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OpenAI’s Losses Doubled to $540 Million as It Developed ChatGPT https://
bit.ly/3M0sdF2 #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Bard’s Hallucinations: Another AI Accuracy Challenge
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So, another one of Bard's hallucinatory trips?
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Three Keys to Faster Better Organizational Decisions
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Three Keys to Faster, Better Decisions https://
mckinsey.com/capabilities/p
eople-and-organizational-performance/our-insights/three-keys-to-faster-better-decisions
… @ASMEdotorg @3DSNorthAmerica @cyngn @MargaretSiegien @3DSdelmia @3DStherese @Cindybolt61 @fogoros @DrFerdowsi @CRudinschi @PawlowskiMario @IIoT_World @MEngineeringMag #Science #Engineering #Technology #SET -
Stanford releases string2string tool for NLP and bioinformatics research
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(3/3) We hope string2string will be a valuable asset for researchers & practitioners across NLP, bioinformatics, CSS, and the digital humanities. Join us in the world of strings! Code: https://
github.com/stanfordnlp/st
ring2string
… Docs: https://
string2string.readthedocs.io/en/latest/ Paper: https://
arxiv.org/abs/2304.14395 -
Stanford NLP releases string2string open-source library
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(1/3) Introducing string2string, an open-source library from StanfordNLP’s Mirac Suzgun (+me & @pmphlt
) for string-to-string problems, w/traditional & neural algorithms for string alignment, distance measurement, lexical & semantic search, similarity analysis, and more! -
Advanced Algorithms for NLP Evaluation and Text Analysis
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(2/3) Notable features include the Smith-Waterman, Hirschberg, Wagner-Fisher, and Knuth-Morris-Pratt algorithms, neural techniques like BARTScore, BERTScore, and Faiss, sacreBLEU & ROUGE for evaluation, and visualization tools & metrics for interpretation and analysis.