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Details:

🎥 Livestream: Zoom starts around 6:20pm BST ⚠️ In Person Form: https://forms.gle/SQCDSoNALpVUJ11N9

The clouds are shining and the pollen allergies are blooming, which can only mean one thing--spring is arriving in London and it's time to gather indoors for talks on LLMOps and more!

Agenda:

⏱️ 6:00 pm onwards - Arrival and networking ⏱️ 6:30 pm - Kick off and welcome with Alex Housley (Founder at Seldon)

Speakers:

🎙️ Navigating LLM Deployment: Tips, Tricks, and Techniques Meryem Arik, CEO & Co-founder TitanML

Join Meryem Arik in a discussion on the best practices in model optimization, serving and monitoring - with practical tips and real case-studies.

🎙️ Cost Optimisation Strategies for ANNA’s AI Accountant: Practical LLM Batching & Prompt Caching Nikolai Turusin, Lead Data Scientist at ANNA

Drawing on ANNA’s experience processing 2 billion tokens each month, with system prompts reaching 50k tokens — we’ll show you how using batch APIs and prompt caching techniques can dramatically cut expenses in production LLM systems.

✨✨✨More Speaker Announcements Coming Soon!✨✨✨

IMPORTANT: You can only register for this event on Eventbrite, here: https://Oct2024LNETM.eventbrite.co.uk/?aff=EHSC

Crossing the chasm between the promise and the reality of new technologies...

We’ve been here before multiple times. A shiny new technology, this time it’s different, yet another paradigm shift. As ever there is a gap between the promise and the reality that we all see on a day-to-day basis.

With this as background, it is a great privilege to welcome Julian Levy (Managing Partner at Elevata Ventures, prominent angel investor and LNETM regular) to present his perspective on what we are seeing from a broader technical and historical viewpoint, look at what is hype and what is real, and provide some interesting views on the direction of travel.

He looks into how we got here and where it is going directionally, making the point that the unit economics of judgement - a formerly solely human activity - have changed and looks into the build out the infrastructure to apply this shift successfully at scale.

Meryem Arik (CEO & Founder of TitanML) will then interview Julian and several industry experts regarding the topics surfaced in the keynote presentation – these experts include:

• Emily Prince (Group Head of Analytics & AI at LSEG)
• Steve Higgon (CEO of TAAP)

There will also be flash talk presentations from two innovative emerging companies:

• TAAP’s AI App Builder that can take high-level specifications and machine-generate enterprise-scale applications, UI, middle tier, SQL, and database, all in less than 60 seconds. This bug-free implementation is deterministic, has no hallucinations, is human-readable, and is extensible, compensating for early-stage AI App Builder limitations.
• Sambanova is focused on helping people build agentic applications which make many calls to LLMs requiring high speed to get responses back in a time that retains interactivity. They offer the Llama 3.1 series including 405B at extremely high speeds (1000/500/>100 tokens per second respectively for the three sizes) and can be deployed via SaaS API, in the cloud and on-premises.

Sincere thanks to London Stock Exchange Group for hosting the LNETM, to TAAP for sponsoring this month’s event and to all our annual sponsors for 2024.

IMPORTANT NOTES:

1. You must register through Eventbrite in order to attend.
2. Registration will close 48 hours before the event (on the night of Tuesday 8th October).
3. Please bring Government Issued photo ID, as it will be required for venue entry.

*** RSVP: https://www.aicamp.ai/event/eventdetails/W2024022210 (Due to limited room capacity, you must pre-register at the link for admission).

Welcome to the monthly in-person AI meetup in London. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers.

Agenda: * 6:00pm\~7:00pm: Checkin, Food/drink and Networking * 7:00pm\~9:00pm: Tech talks and Q&A * 9:00pm: Open discussion and Mixer

Tech Talk: Deploy self-hosted open-source AI solutions Speaker: Dmitri Evseev @Arbitration City Abstract: I will share practical insights from my journey from law firm partner to AI startup founder, focusing on deploying self-hosted, open-source AI solutions in the legal sector and beyond. I will discuss the benefits of self-hosting over third-party APIs, the challenges of implementing these systems for production use, and methods to optimise GPU usage with open-source tools. The talk will also cover approaches to integrate containerised architectures and encryption for secure, scalable AI deployment, aiming to assist the LLMOps community and others exploring self-hosted AI and retrieval-augmented generation (RAG).

Tech Talk: Falcon OS - An open source LLM Operating System Speaker: Heiko Hotz (Google) Abstract: In this talk I will introduce the Falcon OS project, a collaboration with the Technology Innovation Institute and Weights & Biases. Falcon OS is a new operating system project centered around the open-source Falcon 40B LLM. It aims to simplify complex tasks through natural language, bridging the gap between users and computers. This talk will explore its potential to transform AI applications and what it takes for an LLM to be able to reason and act, a key capability for such a system.

Tech Talk: Navigating LLM Deployment: Tips, Tricks, and Techniques Speaker: Meryem Arik (TitanML) Abstract: Self-hosted Language Models are going to power the next generation of applications in critical industries like financial services, healthcare, and defence. Self-hosting LLMs, as opposed to using API-based models, comes with its own host of challenges - as well as needing to solve business problems, engineers need to wrestle with the intricacies of model inference, deployment and infrastructure. In this talk we are going to discuss the best practices in model optimisation, serving and monitoring - with practical tips and real case-studies.

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors: We are actively seeking sponsors to support AI developers community. Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure to our extensive membership base of 10,000+ local or 300K+ developers worldwide.

Community on Slack/Discord - Event chat: chat and connect with speakers and attendees - Sharing blogs\, events\, job openings\, projects collaborations Join Slack (search and join the #london channel) \| Join Discord

Join us at the offices of Datasparq on Wednesday 11th October for an evening of talks, food, and conversation with ML and AI industry pros.

If you can't join us in person you can watch remotely via Google Meet or alternatively watch the recording on our YouTube channel (typically available within 48hrs of the event).

Please RSVP for the event well in advance if you plan to attend in person and unRSVP if you can no longer attend as limited spaces are available.

Agenda

06:30pm - Doors open, food and drink served

07:00pm - Welcome

07:15pm - Jess McQuade (Data Scientist) and Adil Rahman (Senior Data Scientist), Datasparq "Predicting part consumption for aircraft maintenance"

07:55pm - Break

08:10pm - Meryem Arik, TitanML "Deploying LLMs: Bigger Isn't Always Better When It Comes to GPUs"

09:00pm - Wrap up

This event will be available to watch via livestream, more details below Watch livestream on YouTube here

We talked about:

Meryam's background The constant evolution of startups How Meryam became interested in LLMs What is an LLM (generative vs non-generative models)? Why LLMs are important Open source models vs API models What TitanML does How fine-tuning a model helps in LLM use cases Fine-tuning generative models How generative models change the landscape of human work How to adjust models over time Vector databases and LLMs How to choose an open source LLM or an API Measuring input data quality Meryam's resource recommendations

Links:

Website: https://www.titanml.co/ Beta docs: https://titanml.gitbook.io/iris-documentation/overview/guide-to-titanml... Using llama2.0 in TitanML Blog: https://medium.com/@TitanML/the-easiest-way-to-fine-tune-and-inference-llama-2-0-8d8900a57d57 Discord: https://discord.gg/83RmHTjZgf Meryem LinkedIn: https://www.linkedin.com/in/meryemarik/

Free MLOps course: https://github.com/DataTalksClub/mlops-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Putting LLMs in production - Meryem Arik

About this event

Outline:

• LLMs
• Generating labels with LLMs
• Fine-tuning and optimizing LLMs

About the speaker:

Meryem is a recovering physicist and the co-founder of TitanML - TitanML is an NLP development platform that focuses on deployability of LLMs - allowing businesses to build smaller and cheaper deployments of language models with ease.

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