ML and AI Technologists Convene, Connect at ML Ops World
AUSTIN, Nov. 7, 2024 – Leading machine learning (ML) and generative artificial intelligence (AI) technologists from around the globe gathered in Austin today to kick off Day 1 of the in-person global ML Ops World/Gen AI Summit.
Amidst an environment of rapid industry acceleration, ML and AI practitioners are seeking connections, collaborations, best practices, recommendations and tools.
AI Makerspace Co-Founder Greg Loughnane opened the conference with encouragement for technologists to take advantage of the ML Ops community and learn from one another in addition to attending deep-dive sessions on topics ranging from tutorials on building LLM applications to architecting multi-agent systems for code generation.
“It’s always good to learn from others’ experiences,” said Prabhdeep Singh, a ML engineering manager at United Airlines who is working to build and tune a machine learning platform and hopes to learn best practices from the ML Ops community.
“There is ambiguity in the industry – and there are tons of tools,” said Robin Amin, an ML ops engineer at Veterans United, as he gestured toward the conference exhibition hall, where dozens of vendors tout their products and services. “I’m here to see what types of automations other organizations are adopting so that I can select some tools and then develop others.”
Also working to build or coalesce their employers’ ML platforms are an IT leader from Fannie Mae and an ML Ops engineer from Turo.
“Building from the ground up is not a popular or efficient approach,” said Angelica Pando, an engineering manager at Turo who is looking for plug-ins and best practices to help expedite her project.
Cyber Advisor and Evangelist Helen Oakley, CISSP, GPCS, GSTRT, who is founding partner of AI Integrity & Safe Use Foundation, said she is attending the conference to make new connections. The foundation’s work centers around helping organizations build and acquire resilient AI systems.
Denys Linkov, head of ML at Voiceflow, took the main stage to reflect on key advancements made in the ML and AI space in 2024. He discussed multimodal LLMs that combine vision, audio, and other data types, such as Gemini Pro and GPT-4.0, which significantly expand context length and functionality. These advancements, including open-source tools like PaliGem and CoPali, are setting new standards for AI's ability to interact with multiple data forms. Linkov also pointed to human-computer interaction breakthroughs, noting Meta's integration of LLMs within its ecosystem, reaching billions of users worldwide. This trend is furthered by OpenAI's acquisition of Multi, which supports multi-agent systems, and GPT Canvas, enhancing desktop interactivity. In video generation, Linkov noted releases like Runway Gen3 Alpha and Meta’s MovieGen, which have introduced exciting new capabilities, with both closed and open-source options now available to developers.
Also in 2024, we have seen the rise of MegaGPU clusters, he said. These vast supercomputing networks, such as Elon Musk’s Colossus, are built to support complex AI models but face challenges with power demands and reliability.
Linkov underscored the importance of evaluations in AI model performance, with major vendors like Anthropic, Cohere, Google, and OpenAI launching platforms for evaluating and optimizing AI models. This focus on evaluation tools reflects the industry’s need for precise measurement in GenAI. He also discussed how automation remains central to AI's future, with companies like Google and Amazon leveraging AI-driven automation in tasks such as Java migration and customer support, despite return on investment (ROI) not being the primary focus initially. And he emphasized the emergence of synthetic data as a pivotal resource, as demonstrated in the Llama 3 paper.
Stay tuned for more to come tomorrow from the ML Ops World – Gen AI Summit in Austin!
AUSTIN, Nov. 7, 2024 – Leading machine learning (ML) and generative artificial intelligence (AI) technologists from around the globe gathered in Austin today to kick off Day 1 of the in-person global ML Ops World/Gen AI Summit.
Amidst an environment of rapid industry acceleration, ML and AI practitioners are seeking connections, collaborations, best practices, recommendations and tools.
AI Makerspace Co-Founder Greg Loughnane opened the conference with encouragement for technologists to take advantage of the ML Ops community and learn from one another in addition to attending deep-dive sessions on topics ranging from tutorials on building LLM applications to architecting multi-agent systems for code generation.
“It’s always good to learn from others’ experiences,” said Prabhdeep Singh, a ML engineering manager at United Airlines who is working to build and tune a machine learning platform and hopes to learn best practices from the ML Ops community.
“There is ambiguity in the industry – and there are tons of tools,” said Robin Amin, an ML ops engineer at Veterans United, as he gestured toward the conference exhibition hall, where dozens of vendors tout their products and services. “I’m here to see what types of automations other organizations are adopting so that I can select some tools and then develop others.”
Also working to build or coalesce their employers’ ML platforms are an IT leader from Fannie Mae and an ML Ops engineer from Turo.
“Building from the ground up is not a popular or efficient approach,” said Angelica Pando, an engineering manager at Turo who is looking for plug-ins and best practices to help expedite her project.
Cyber Advisor and Evangelist Helen Oakley, CISSP, GPCS, GSTRT, who is founding partner of AI Integrity & Safe Use Foundation, said she is attending the conference to make new connections. The foundation’s work centers around helping organizations build and acquire resilient AI systems.
Denys Linkov, head of ML at Voiceflow, took the main stage to reflect on key advancements made in the ML and AI space in 2024. He discussed multimodal LLMs that combine vision, audio, and other data types, such as Gemini Pro and GPT-4.0, which significantly expand context length and functionality. These advancements, including open-source tools like PaliGem and CoPali, are setting new standards for AI's ability to interact with multiple data forms. Linkov also pointed to human-computer interaction breakthroughs, noting Meta's integration of LLMs within its ecosystem, reaching billions of users worldwide. This trend is furthered by OpenAI's acquisition of Multi, which supports multi-agent systems, and GPT Canvas, enhancing desktop interactivity. In video generation, Linkov noted releases like Runway Gen3 Alpha and Meta’s MovieGen, which have introduced exciting new capabilities, with both closed and open-source options now available to developers.
Also in 2024, we have seen the rise of MegaGPU clusters, he said. These vast supercomputing networks, such as Elon Musk’s Colossus, are built to support complex AI models but face challenges with power demands and reliability.
Linkov underscored the importance of evaluations in AI model performance, with major vendors like Anthropic, Cohere, Google, and OpenAI launching platforms for evaluating and optimizing AI models. This focus on evaluation tools reflects the industry’s need for precise measurement in GenAI. He also discussed how automation remains central to AI's future, with companies like Google and Amazon leveraging AI-driven automation in tasks such as Java migration and customer support, despite return on investment (ROI) not being the primary focus initially. And he emphasized the emergence of synthetic data as a pivotal resource, as demonstrated in the Llama 3 paper.
Stay tuned for more to come tomorrow from the ML Ops World – Gen AI Summit in Austin!
