The Enterprise AI Show

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LLMOps & Conversational Intelligence for AI Dec 06, 2023

Show notes

GUEST: Alex Kvamme (@KwameKvamme, CEO @GetPathlight) talks about using AI to unlock market insights from discussions with customers and partners.

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Topic 1 - Welcome to the show. Alex, Tell us a bit about your background.
Topic 2 - What is the concept of conversational intelligence and how does it apply to most organizations today? What problem is it trying to solve?
Topic 3 - I would think there is a trade off between time and resources to get to a customer issue vs. the value of that insight. How does an organization weigh the opportunity cost? How do you keep the insights generated from being overwhelming
Topic 4 - Let’s move from the concept to practical. Where is the data in most organizations today that will yield results and solve problems? How would you suggest folks get started and what use case are they likely to implement first? Is this data that humans either can’t or won’t get too because it is an enormous amount or maybe too tedious to pay for?
Topic 5 - How does all of this work under the hood? Is this one model or multiple models working in parallel? Is there a framework for the operations and lifecycle managed by an organization?
Topic 6 - Let’s talk about what it takes to get an LLM into production. The the rise of LLM’s and foundational models such as Llama2, there is an interest for organizations to use LLM’s, but going from concept to production still has a high barrier to entry. It’s easy to download a model, it’s much harder to either fine-tune it or set up RAG with a vector database for your specific use case. Would you agree and what are your thoughts?

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From Cloud to Cloud-native to COVID Dec 03, 2023

Show notes

How did the modern cloud evolve from the earliest days of AWS to today’s AI boom? What roles did open source, mobile apps, microservices and the sharing economy play?

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SHOW NOTES:

All the show notes from this week's show.
2001 - a dotCom Bubble Odyssey (Part 1 of 3)
Building the Foundations of Modern Cloud (Part 2 of 3)

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Culture, Teams and Adoption of FinOps Nov 29, 2023

Show notes

Gary Harmson (Principal Customer Engineer @Google) and Ieva Jonaityte (Technical Account Mgr @DoIT) talk about the team dynamics, culture and training that drive FinOps success.

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SHOW NOTES:

DoIT Homepage
Simplifying FinOps for AI Workloads (Eps.719)
Leveraging FinOps to Scale a Startup (Eps. 761)
DIKW Pyramid - Framework for data classification

Topic 1 - Welcome to the show and back to the show. Gary, tell us about your background and what areas you focus on at Google Cloud these days.

Topic 2 - Let’s begin by talking about language, specifically the gaps in language (and understanding) between engineering teams and finance teams. What works today and where are the biggest gaps and challenges?

Topic 3 - One of the challenges of Cloud billing, and hence FinOps, is the 100s or 1000s or line-items. What are they for? How are they changing? What are some of the things/tools out there to make sense of all of this spend? (e.g. visualization, tagging, etc.)

Topic 4 - We’re all familiar with budgeting (pre-activity) and complaints about project/cost overruns (post-activity), but what are some of the things happening mid-project, or on-going to avoid the surprises or overruns?

Topic 5 - How much of these on-going changes/tracking is done by the engineering teams and how much is being done by finance teams?

Topic 6 - Can you share with us examples of how companies have evolved with good FinOps principles and hygiene in place?

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Building the Foundations of the Modern Cloud Nov 26, 2023

Show notes

How did the 2001 dotCom bubble burst lead to the 2008 housing crisis and how did it impact the technology markets? And the OpenAI Coup-oops!

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Learn More About Azure Offerings : Learn more about Azure Migrate and Modernize & Azure Innovate!
Azure Free Cloud Resource Kit : Step-by-step guidance, resources and expert advice, from migration to innovation.
Code Comments - An original podcast from Red Hat (Season 2)
Adjusting to new technology, from teams that have been through it
Find "Breaking Analysis Podcast with Dave Vellante" on Apple, Google and Spotify
Keep up to data with Enterprise Tech with theCUBE

SHOW NOTES:

All the background research for the show

A BRIEF SUMMARY OF THE OPEN AI COUP ATTEMPT

Sam Altman (CEO) got fired, then returned

HOW DID DOTCOM BUBBLE LEAD TO HOUSING CRASH AND CLOUD?

Google made Internet advertising available to every business
SaaS companies emerge, to replace core business functions
The “sharing economy” took off (music, pictures, blogs, etc.)
Shadow IT caused problems for Corporate IT

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Behind the scenes of building Platform Engineering Nov 22, 2023

Show notes

Can you still call them the FAANG companies considering Facebook is now Meta and Google is now Alphabet? Maybe it’s MAANA now?! Elliott Clark (CEO/Founder, Batteries Included) talks about creating a Platform Engineering org and building an IDP before it was cool.

SHOW: 773

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Learn More About Azure Offerings : Learn more about Azure Migrate and Modernize & Azure Innovate!
Azure Free Cloud Resource Kit : Step-by-step guidance, resources and expert advice, from migration to innovation.
CloudZero – Cloud Cost Visibility and Savings
CloudZero provides immediate and ongoing savings with 100% visibility into your total cloud spend
Datadog Kubernetes Solution: Maximum Visibility into Container Environments
Start monitoring the health and performance of your container environment with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.
Datadog Synthetic Monitoring: Frontend and Backend Modern Monitoring
Ensure frontend issues don’t impair user experience by detecting user-facing issues with API and browser tests with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.

SHOW NOTES:

Topic 1 - Welcome to the show. Elliott, you have some great experiences at Cloudera and Meta/Facebook that shaped you moving out to start your own thing at Batteries Included. Give everyone a brief background please.
Topic 2 - You were building Internal Developer Platforms (IDP) and doing Platform Engineering before it was cool. Tell everyone a little about the need and how it came to be at Meta/Facebook.
Topic 3 - I think it’s probably important to talk about the origin stories for this. What was the problem to solve? How was it solved? What was the final “product” and how was it used?

Topic 3a - Anything you would have done differently?
Topic 4 - We always hear stories about the FAANG companies and the scale they operate in. But, we hear mixed things about if following those practices are a good idea. Some say we should use them because we know it is repeatable at scale. Others say the practices are only relevant at those companies and most organizations don’t need that level of complexity. Thoughts? What are the pros and cons?
Topic 5 - What are your thoughts on the current and future state of Platform Engineering and Internal Developer Platforms? There seems to be a tension between being prescriptive or opinionated enough for operations to scale vs. developers needing to use the tools they know and love to be as productive as possible. Thoughts?
Topic 6 - Let’s talk about Open Source. Many have heard about Backstage when it comes to Platform Engineering and we’ve even talked about it on this show before. What are your thoughts around building these platforms on OSS. Also, any thoughts on OSS being cost prohibitive?
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2001- a DotCom Bubble Odyssey Nov 19, 2023

Show notes

What happened in the lead-up to the Internet Bubble burst of 2001? What went right, what went wrong, and what lessons did we learn? (Part 1 of 3)

SHOW: 772

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Find "Breaking Analysis Podcast with Dave Vellante" on Apple, Google and Spotify
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Code Comments - An original podcast from Red Hat (Season 2)
Adjusting to new technology, from teams that have been through it

SHOW NOTES:

All the Shows Notes Research

Original Tweet that inspired the show: https://x.com/forrestbrazeal/status/1719827334834913283?s=20

“Looking for recommendations: what’s the best book ever written about the dotcom bubble? Specifically looking for something that captures the emotions of that time as well as the mechanics”

THE BROWSER, THE NETWORKS, THE CARRIERS AND POSSIBILITIES

Information was freely exposed to the Internet (and Intranets)
It was Digital Transformation 1.0 era - Everything on the Internet
The New Industrial Revolution
Lots of focus on new Online Purchasing
Lots of focus on new Telecommunications services (VoIP, VoD, etc.)
Lots of focus on new media partnerships

EVERYTHING ALWAYS GOES UP, EVERYDAY, RIGHT?

Massive network build outs
Lots of Engineers and MBAs moved out to Silicon Valley
Every startup built their own data-centers, networks, applications, etc.
IPOs were happening every week
Telecom vendors vs. Internet/Networking vendors
Stock prices going up $1-2 per day

LESSONS LEARNED:

Infrastructure has to match the ambitions
Business models always come back to revenues and profitability
Each wave can create the new big winners (and losers)
Understand Manias vs. Fundamentals (where in the wave are we?)
Stupid money eventually finds a bottom

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Intro to Vector Databases Nov 15, 2023

Show notes

Jeff Huber (@jeffreyhuber, Founder/CEO @trychroma) talks vector databases, data integration, RAG, Embedded models, and AI integration.

SHOW: 771

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Start monitoring the health and performance of your container environment with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.
CloudZero – Cloud Cost Visibility and Savings
CloudZero provides immediate and ongoing savings with 100% visibility into your total cloud spend

SHOW NOTES:

Topic 1 - Welcome to the show. Tell us a little bit about your background, and what brought you to create Chroma.

Topic 2 - Our audience, like many out there, is learning AI as fast as they can. So, let’s start with a few basic concepts. What is a vector database, and why is it important to AI?

Topic 3 - Does this only help foundational models? What goes into the integration into a model, and can this be used with any model?

Topic 4 - Is RAG (Retrieval-Augmented Generation) possible without a vector database?

Topic 5 - What are the trade-offs between fine-tuning a model (adding the data in) vs. RAG (keeping the data external)?

Topic 6 - What else is needed to create an “AI Stack”?

Topic 7 - Let’s talk about Chroma. First off, there is the OSS project which has been a huge success. Over 3 million downloads and 9.5k Github stars and inclusion into some 10k plus projects. Tell everyone a little bit about Chroma and what makes it different. You recently also announced a major milestone, over one million instances running

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Is AI the new Oppenheimer event? Nov 12, 2023

Show notes

AI is reaching the point where there is wild speculation, potential regulations, and opinions on if it will destroy humanity. So how does anyone make sense of all of it?

SHOW: 770

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SHOW SPONSORS:

Code Comments - An original podcast from Red Hat (Season 2)
Adjusting to new technology, from teams that have been through it
Find "Breaking Analysis Podcast with Dave Vellante" on Apple, Google and Spotify
Keep up to data with Enterprise Tech with theCUBE

SHOW NOTES:

OpenAI’s former top safety researcher says there’s a ’10 to 20% chance’ that the tech will take over with many or most ‘humans dead’
The Dawn of the AI Era 2022-2023 (Acquired Podcast)
An AI Capitalist Primer
Techno-Optimist Manifesto (a16z)
The AI Bill of Materials (Redmonk)
US Gov’t Executive Offer on Safe, Secure, Trustworthy AI (Oct 2023)
Regulating AI by Executive Order (Steven Sinofsky)
The Philanthropy of Silicon Valley
“The Trolley Problem”

ARE WE UNDER OR OVER REACTING TO THE AI POSSIBILITIES?

Oppenheimer said the possibility of destruction was “near zero”
OpenAI research said it’s 10-20% chance of human destruction

WHAT ARE THE OPEN, REGULATIVE AND STRUCTURAL GUARDRAILS OF AI

What is good or bad with AI?
Should societal concerns be considered? By whom?
Should environmental concerns be considered? By whom?

FEEDBACK?

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Testcontainers to Reduce Developer Frustration Nov 08, 2023

Show notes

Eli Aleyner (@ealeyner, Co-founder at @AtomicJarInc) talks about the issues with shifting left and how to reduce developer frustration with Testcontainers.

SHOW: 769

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SHOW SPONSORS:

CloudZero – Cloud Cost Visibility and Savings
CloudZero provides immediate and ongoing savings with 100% visibility into your total cloud spend
Datadog Security Solution: Modern Monitoring and Security
Start investigating security threats before it affects your customers with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt

SHOW NOTES:

Topic 1 - Welcome to the show. Tell us a little bit about your background, and what brought you to create AtomicJar
Topic 2 - Let’s start at the beginning. We hear more and more about shifting everything left. In this case we are talking about potentially shifting testing left. What problem are we trying to solve and everything comes at a cost, what are the tradeoffs?
Topic 3 - We hear all the time that adoption of changes to a development practice is part culture and part technology. What is the hook that gets folks interested in investing time and resources into better testing practices?
Topic 4 - Are the tests integrated into the code? How seamless is this into existing CI/CD pipelines or an organization's DevOps practice on average?
Topic 5 - From a business perspective, how are the advantages typically measured? More deployments, less defects, etc
Topic 6 - Let’s talk about the OSS project Testcontainers a bit. What is it? How did it come about? How are folks using this concept of throwaway, lightweight instances of databases, message brokers, and web browsers, for instance. Is this all in Docker containers?
Topic 7 - There’s also testing in the cloud with a SaaS service (Testcontiners Cloud). What is the origin story behind this and how are folks using it today? Is this a replacement for say Docker Desktop?
Topic 8 - For those out there that are interested? How would they get started?

FEEDBACK?

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The Challenges of Pre-Announcements Nov 05, 2023

Show notes

Your favorite product just announced something new and you’re upset. Why didn’t they tell you about it ahead of time? Why didn’t they ask for your feedback? How does a launch work?

SHOW: 768

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