Codetown ::: a software developer's community
Time: September 14, 2009 to September 16, 2009
Location: Hilton Boston Logan Airport
Street: 1 Hotel Drive
City/Town: Boston, MA
Website or Map: http://maps.google.com/maps?f…
Event Type: conference
Organized By: Ajaxian.com
Latest Activity: Jul 1, 2009
Ajaxian.com's The Ajax Experience comes to Boston, September 14 - 16, 2009. Whether you're an Ajax newbie or expert, you will benefit from over 50 essential sessions and tutorials from Ajax framework founders, contributors, project leads and entrepreneurs.
- New to the Web 2.0 world? Attend tutorials, and benefit from introductory sessions on all the major frameworks and tools.
- Ready to take your intermediate skills to the next level? Learn how to develop better software in your everyday development career with exclusive insight into the next round of framework releases, performance best practices, security threats and more.
- Are you an Ajax expert? TAE provides a gathering place for community experts to meet and push forward Web development techniques while giving more advanced developers opportunities to expand their areas of focus.
View the can't-miss agenda, all-star speaker lineup and register online.
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
Check out the Codetown Jobs group.
According to Camilla Montonen, the challenges of building machine learning systems are mostly creating and maintaining the model. MLOps platforms and solutions contain components needed to build machine systems. MLOps is not about the tools; it is a culture and a set of practices. Montonen suggests that we should bridge the divide between practices of data science and machine learning engineering.
By Ben LindersThis insightful InfoQ article dispels the common myths surrounding Lambda Cold Starts, a widely discussed topic in the serverless computing community. As serverless architectures continue to gain popularity, misconceptions about Lambda Cold Starts have proliferated, often leading to confusion and misguided optimization strategies.
By Mohit PalriwalJules Damji discusses which infrastructure should be used for distributed fine-tuning and training, how to scale ML workloads, how to accommodate large models, and how can CPUs and GPUs be utilized?
By Jules DamjiGitHub has released two features to improve the security and resilience of repositories. The first feature allows Dependabot to run as a GitHub Actions workflow using hosted and self-hosted runners. The second release introduces the public beta of Artifact Attestations, simplifying how repository maintainers can generate provenance for their build artifacts.
By Matt CampbellMeta AI released Llama 3, the latest generation of their open-source large language model (LLM) family. The model is available in 8B and 70B parameter sizes, each with a base and instruction-tuned variant. Llama3 outperforms other LLMs of the same parameter size on standard LLM benchmarks.
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