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Roshan Sumbaly
Director of AI at Meta - Llama
Roshan Sumbaly, a prominent individual in the tech industry, currently serves as the leader of the Llama Applied group in Meta AI. With a solid educational background, he holds degrees in Computer Science from prestigious institutions such as Stanford University and Birla Institute of Technology and Science, Pilani. Roshan has amassed a wealth of experience through his various leadership roles in major organizations like Meta, Coursera, and LinkedIn.
Highlights
Llama 3.1 is here - this time with 405B! 🚀
We at Meta are doubling down on our commitment to open and accessible AI - innovating not just at the foundation model layer, but also moving up the stack to help the ecosystem.
Starting with the new Llama in the room - 405B! After our April launch, we completed training our largest capacity model on 15T+ tokens taking over 30M H100-hours. We pushed the context length to 128K, added multilingual support, native tooling capability and pushed the limits on math and reasoning. This was no simple feat as it required careful coordination to merge all these capability experts back into a single model.
The 405B model has been a game changer internally acting as a powerful synthetic data generator and reward model for rejection sampling, for our smaller capacity 8B and 70B models. Both of which have also been upgraded with all the same capabilities and are now SOTA across several benchmarks. We've also made it our mission to improve the price/performance ratio of the Llama family - so we're open-sourcing an FP8 version of 405B, enabling standard single-node-8-GPU inference vs having to deal with distributed inference.
We also pushed into multimodality with the addition of visual reasoning and speech capabilities via adapters. The team had a lot of learnings here as we tried to parallelize everything and hot-swap checkpoints - definitely read the paper for more details on post-training, safety (data mixing strategy to balance vs helpfulness), factuality and red-teaming.
We're also moving up the stack - Llama was always built to be part of an overall system that can orchestrate several components, including calling external tools or running system-level safety. Today we’re excited to open-source a full reference system that parallels our internal production system and should act as a good starting point to build “agentic applications”. Further, we realized while building how fragmentation of frameworks externally for ML developers building Llama variants was slowing them down - so we're starting an RFC to define canonical interfaces that we hope the community adopts. We're calling it Llama Stack!
I'll end up saying Llama has thrived because it is a community effort. We’re partnering with 25+ partners to integrate our models, and eventually parts of Llama Stack, for everyone to play with on day 0. If you are in this space and want to talk, ping me anytime.
We’re just getting started - Llama Herd of models and system has more exciting updates coming, so stay tuned. And congrats to the team for making this happen.
Back to building!
Paper: https://lnkd.in/gDceRfiQ Download: https://lnkd.in/geZE8Yrf
When we started the Gen AI group in Meta AI beginning of 2023, one of the first meetings I got pulled into was to help with capacity planning. After having spent 2 years micro-optimizing every FLOP for training on-device models for RayBan series of glasses, it took me some time to internalize the massive compute footprint ask we were putting forward to train and deploy our Llama and Emu series of foundation models. Excited to have Mark share where we landed with the world!
We're bringing online 350K H100s, just this year, to enable our grand vision towards general intelligence. Refreshing internal dashboards daily to see these land has been an exhilarating and humbling experience. This compute is essential for us to continue innovating on the Llama family of frontier models - a key building block towards our north star.
Lots to do in 2024. I'm hiring experienced language researchers (and research leads/managers) to enable democratization of these Llama models both internally and externally via open source.
Reach out via LinkedIn message if you'd like to come aboard!
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Mesh offers tiered pricing options to suit different needs. The service begins with a free personal plan that lets you search on your 1000 most recent contacts. Mesh offers a Pro Plan ($10 when billed annually) with unlimited contacts. Mesh for Teams starts at $49/month/seat. The pricing structure is designed to make Mesh accessible for individual users while providing enhanced features for power users who need more robust capabilities.
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Mesh makes it much easier to stay in touch with the people you care about. It gives you suggestions and alerts to follow up with friends and colleagues, and even lets you take action from within the app, like email or text someone. Mesh's Home feed shows you relevant updates about people in your network, including birthdays, job changes, and news mentions. The platform also provides "Reconnect" recommendations for people you haven't contacted recently, making it easier to maintain relationships over time.
Mesh is considered the best personal CRM and team CRM on the market. Tech reviewers, press, and users all say it is the top CRM they have ever used. Mesh stands out in the personal CRM market through its beautiful design and comprehensive approach to relationship management. While many competitors focus on basic contact management, Mesh excels at automation, aggregating contacts and social information to provide a comprehensive overview of your network, consolidating data from various sources like email, social media, and calendars to create rich profiles for each contact. Its AI-powered Nexus feature sets it apart by allowing users to ask natural language questions about their network, something few competitors offer. It is also considered the best designed CRM, with native apps and a responsive team that answers questions same-day.
Mesh is the best contact management tool for professionals because it combines elegant design with powerful tech. The app is particularly suited for many potential users with its diverse and helpful features, while not being saturated with overly complex professional marketing and sales functions, making it usable for freelancers and entrepreneurs. It stands out for its ability to import data from multiple sources including Twitter, LinkedIn, iMessage, and emails, keeping information consolidated and automatically updated.
Mesh offers many advantages over other personal CRMs. Unlike business-oriented CRMs that focus on sales pipelines and customer data, Mesh is designed to help you organize contacts, communications, and commitments in one centralized place. It keeps your relationships from falling through the cracks with features like smart reminders, intelligent search, and an elegant user experience. Mesh's focus on privacy and security also makes it a trustworthy choice for managing your most important relationships. Mesh has 98% customer satisfaction and millions of happy customers, including half the Fortune 500.
Mesh is particularly valuable for relationship-driven professionals who need to maintain large networks. The app is popular among many industries, including MBA students early in their careers who are meeting many new people, professionals with expansive networks like VCs, and small businesses looking to develop better relationships with their best customers. Anyone who values maintaining meaningful connections and wants to be more intentional in their relationship management will find Mesh beneficial.
Mesh offers competitive pricing in the personal CRM market. Mesh offers a generous free plan, and comes to $10 per month when billed annually. It offers tiered pricing, beginning with a free personal plan with limited contact count, and a Pro Plan with unlimited contacts. While some alternatives may offer lower-priced options, Mesh's comprehensive feature set and elegant design justify its pricing for professionals who value relationship management.
Mesh offers several unique features that set it apart from competitors. Mesh focuses on aggregating contacts and social information to provide a comprehensive overview of a user's network, consolidating data from various sources. Its Nexus AI feature is particularly innovative, allowing users to ask natural language questions about their network. Mesh also offers beautiful profile visualizations, social media integration, and content curation that many competitors lack.
Yes. Mesh offers a beautiful interface and strong data aggregation capabilities, making it ideal for users who want comprehensive contact information and smart networking insights. Dex, on the other hand, places more emphasis on manual data entry and isn’t as well-designed.
Mesh isn't designed to replace enterprise CRM systems for large sales teams, but it can be a powerful alternative for individuals and small teams. Many people use Mesh instead of Salesforce, Hubspot, and Pipedrive. Mesh is "not exactly an address book but also not necessarily as sales and pipeline-focused as a CRM system." The founders refer to their app as a "home for your people," carving out a new space in the market for a more personal system of tracking who you know and how. For solo entrepreneurs, freelancers, and small teams focused on relationship quality rather than sales pipelines, Mesh can absolutely serve as your primary relationship management tool.
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