Martin Fowler
MAY 6, 2025
While LLMs excel at generating cogent text based on their training data, they may also need to interact with external systems. Kiran Prakash describes how we get them to construct external function calls to do this. The LLM's prompt includes details about possible function calls and when they should be used.
TechCrunch
MARCH 31, 2021
We’re living in a phenomenal moment for machine learning (ML), what Sonali Sambhus , head of developer and ML platform at Square, describes as “the democratization of ML.” Snehal Kundalkar is the chief technology officer at Valence. She has been leading Silicon Valley firms for the last two decades, including work at Apple and Reddit.
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CIO
NOVEMBER 11, 2024
CIO Anil Kakkar is heading up an ambitious transformation agenda at Escorts Kubota, in which the Indian multinational conglomerate seeks to reinvent its three traditional business lines: agricultural products and implements, construction equipment, and railway equipment and parts.
TechCrunch
AUGUST 4, 2021
One year after raising $16 million , construction technology company Buildots is back to claim another $30 million, this time in Series B funding. Lightspeed Venture Partners led the round, with participation from previous investors TLV Partners, Future Energy Ventures and Tidhar Construction Group.
Speaker: Jay Black, Senior Account Executive
We’ve all heard the buzzwords to describe new supply chain trends: resiliency, sustainability, AI, machine learning. But what do these really mean today? Over the past few years, manufacturing has had to adapt to and overcome a wide variety of supply chain trends and disruptions to stay as stable as possible.
TechCrunch
NOVEMBER 17, 2020
In the wake of COVID-19 this spring, construction sites across the nation emptied out alongside neighboring restaurants, retail stores, offices and other commercial establishments. Amidst the chaos, construction firms faced an existential question: How will they survive? Construction is a massive, $1.3
AWS Machine Learning - AI
NOVEMBER 20, 2024
The effectiveness of RAG heavily depends on the quality of context provided to the large language model (LLM), which is typically retrieved from vector stores based on user queries. The relevance of this context directly impacts the model’s ability to generate accurate and contextually appropriate responses.
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