3 Trends Shaping the Madness of March

John Yue (CEO & Co-Founder @ inference.ai) discusses AI workload sizing, matching GPUs to workloads, availability of GPUs vs. costs, and more.SHOW: 815CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS"SHOW NOTES:Inference.ai (homepage)TechCrunch postSiliconAngle post on ChatGPUTopic 1 - Our topic for today is sizing and IaaS hosting for AI/ML. We’ve covered a lot of basics lately, today we’re going to dig deeper. There is a surprising amount of depth to AI sizing, and it isn’t just speeds and feeds of GPUs. We’d like to welcome John Yue (CEO & Co-Founder @ inference.ai) for this discussion. John, welcome to the showTopic 2 - Let’s start with sizing, I’ve talked to a lot of customers recently with my day job, and it is amazing how deep AI/ML sizing can go. First, you have to size for training/fine-tuning differently than you would for the inference stage. Second, some just think, pick the biggest GPUs you can afford and go. How should your customers approach this? (GPU’s, software dependencies, etc.)Topic 2a - Follow-up question what are the business side, what are the business parameters that need to be considered? (budget, cost efficiency, latency/response time, timeline, etc.)Topic 3 - The whole process can be overwhelming and as we mentioned, some organizations may not think of everything. You recently announced a chatbot to help with this exact process, ChatGPU. Tell everyone a bit about that and how it came to be.Topic 4 - This is almost like a match-making service, correct? Everyone wants an H100, but not everyone needs or can afford an H100.Topic 5 - How does GPU availability play into all of this? NVIDIA is sold out for something like 2 years at this point; how is that sustainable? Does everything need to run on a “Ferrari class” NVIDIA GPU?Topic 6 -  What’s next in the IaaS for AI/ML space? What does a next-generation data center for AI/ML look like? Will the Industry move away from GPUs to reduce dependence on NVIDIA?FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

For some strange reason, “maintenance” has been in the news quite a bit lately. Is there ever a time when maintenance is enjoyable, or appreciated? SHOW: 814SHOW TRANSCRIPT: The Cloudcast #814SHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW NOTES:AWS increased the price of longer-running EKS clusters by 6xBroadcom changes VMware licensing from perpetual to subscriptionBroadcom offers security patches to perpetual license customersIncreasing the Kubernetes support window to 1 yearDiscovering the XZ backdoor (Oxide and Friends, podcast)IS MAINTENANCE EVER APPRECIATED OR ENJOYABLE?Spent the day surrounded by maintenance activities (oil, AC, power-wash)The costs of maintenance are real and opportunityMaintenance often goes unappreciated and unseenNaming: Release Notes, Technical Debt, Chaos EngineeringTECHNICAL DEBT VS. MAINTENANCEShould we encourage a lack of maintenance vs. innovation as a priority?Should we encourage active maintenance with lower hard costs?Is there a way to put respect on maintenance? (e.g. OSS maintainers)Do we undervalue maintenance (e.g. Backup/Recovery, DisasterRecovery, etc.)?What maintenance best practices do you use? What are the good and bad of them?FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Kalyan Veeramachaneni (@kveeramac, CEO/Founder @DataCebo) discusses the generation and value proposition of synthetic data for GenAI.SHOW: 813CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS"SHOW NOTES:DataCebo (homepage)Synthetic Data Vault - SDVTechCrunch ArticleMIT News ArticleTopic 1 - Our topic for today is synthetic data. While the concept and need for synthetic data has been around for a long time, it isn’t a topic that typically comes to the forefront and something we haven’t talked about until today. Today is a bit of crossing the streams between developers and testing data and using GenAI to achieve this goal. For this, we’re joined by Kalyan, CEO and Co-Founder of DataCebo. Welcome to the showTopic 2 - First, for those not familiar, what is synthetic data? What is the use case and need? What problem is it solving today?Topic 2a - Hopefully, listeners out there are making the connection to the advantages of GenAI for synthetic data, but take us through your original concept at MIT and the history of Synthetic Data Vault (SDV).Topic 3 - We recently did a show on the security and privacy of training LLMs where we covered the need to mask PII for the training of models for compliance. I can also see bias issues coming into play or maybe training data that doesn’t exist in the real world (weather models example). What are some of the use cases that you’ve seen require synthetic data sets. Are there certain industries (healthcare, financials, etc.) that benefit?Topic 4 - You were designing this based on GenAI before GenAI was “cool”. How has the rise of LLMs impacted this space?Topic 5 - If I understand this correctly, organizations would put generative AI on a problem to describe a need for a data set, the model would then evaluate the available data and create a quality synthetic or “fake” dataset. How would the organization verify the quality of the dataset? How would they validate that a synthetic data set is as good as the original data?Topic 6 - Let’s talk about resources for a bit. When I think of GenAI and training, I think of large amounts of hardware and in particular GPU’s that might have limited availability. Is that true here? Also, is this on-prem or in the cloud, or both? FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

With the AI Era upon us, the challenge of trying to learn and make sense of the technologies, the business opportunities and the pitfalls is both exciting and equally terrifying.  SHOW: 812SHOW TRANSCRIPT: The Cloudcast #812SHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW NOTES:WHEN WAS THE LAST TIME YOU REALLY LEARNED SOMETHING NEW IN TECH?Cloud was all new, but not completelyThe pace of cloud innovation seemed fast, but not in comparison to AIThe focus was around one cloud vs. a new source every weekPICK A TOPIC, READ, BE CONFUSED, LOOK FOR CONFIRMATION, RINSE, REPEATWhere to start the learning process? Where to pick a source of learning?(Coursera, MIT online, blogs/videos/search, etc.)How to determine legitimacy of the sources? How far to learn before stopping to make sense? Trying to relate it to something you already know? How and when to ask questions? FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Brad Winett (President/Co-founder @TrackItCloud) talks about platforms for entertainment and media. Topics include use cases, partnering with AWS, and creation and consulting services. We even dig into AR and VR a bit at the end.SHOW: 811CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS"SHOW NOTES:TrackIt (homepage)Topic 1 - Our topic for today is media and entertainment in the cloud. I don’t believe we have ever done a show specifically on this topic, and there are some considerations worth talking about. For today, we have Brad Winett, President and Co-founder at TrackIt. Brad, welcome to the show. Let’s jump right in. The media industry as a whole has undergone major change, just like many others. Most of us see it from the consumer end as a cord-cutter. What made you jump into this market and this industry specifically?Topic 2 - Platforms and content distribution in the early days of cloud was a differentiator. I think back to Netflix, they initially had a market advantage because they were able to scale better and to more devices than anyone and even open sourced a number of internally developed items and were the AWS poster child. Over time, these user experiences have become the norm. How should people out there think about media platforms? Are we past the days of build your own?Topic 3 - What about use cases? Media streaming is pretty broad. What does a normal customer look like? Is this big streaming services, smaller companies, etc?Topic 4 - How much of the tech stack is AWS products and how much of the stack is custom typically? Walk us through what a media streaming stack looks like. How is this different from a SaaS provider providing a turnkey service?Topic 5 - I know TrackIt is a big AWS partner. Give everyone an overview of the landscape of AWS Partnership these days. Do you provide mainly professional services and consulting? Topic 6 - Where does open-source software fit into this?Topic 7 - I feel the standard last question these days is how AI will potentially enhance or impact this is some way.FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

What will be the adoption patterns for AI within the Enterprise? Will it follow the early days of Cloud Computing, or will new and different patterns emerge? SHOW: 810SHOW TRANSCRIPT: Cloudcast #810 SHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW NOTES:WHAT WERE THE PATTERNS FOR ENTERPRISE IT AND CLOUD?Shadow ITHigh-scalability or Short-term Projects (and experimentation)Migration via “Cloud First” initiativesDifficult stuff came lastWHAT’S DIFFERENT ABOUT AI vs. CLOUD?CPU to CPU was easier to calculate vs. CPU + GPUHave we learned any lessons about how to value people's productivity?Does Enterprise AI need a Crawl, Walk, Run scenario? Do they need to be sequential and linked? Are Enterprise AI use-cases well defined? How long is the Enterprise willing to fail at experiments? What’s the Enterprise tolerance for GenAI “flaws” (e.g. hallucinations, lack of citations, etc.)Will GenAI rejuvenate Predictive AI projects in the Enterprise? FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Aaron (@aarondelp) and Brian (@bgracely) discuss the biggest tech stories, announcements, and trends from March 2024.SHOW: 809SHOW TRANSCRIPT: https://bit.ly/cloudcast-809-transcriptCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS"SHOW NOTES:LINKS TO ALL THE ARTICLES FOR MARCH 2024 CLOUD NEWS Segments Covered in the Show:Good Old Fashioned Cloud NewsThe AI Innovation Continues - Speed RoundTrend 1 - KubeCon EU 2024Trend 2 - Microsoft continues to branch out from OpenAI as a partnerTrend 3 - NVIDIA held a pretty massive GTC eventFEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Let’s dig into the mindset behind the VMware price increases that have been happening since Broadcom acquired the company in 2023. SHOW: 808CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Want to win a Tesla Cybertruck or $100,000? Enter the WS02 Choreo Code Challenge (before April 30th)WSO2 Choreo - Why build a platform? Just add developers insteadSHOW NOTES:What VMware might look like under Broadcom (Eps.629, June 2022)What to do about VMware (Day Two Cloud, Feb 2024)VMware 10X Price Increase Leaves Companies Looking for AlternativesVMware pricing in the Broadcom EraBROADCOM IS FITTING VMWARE INTO THEIR BUSINESS MODELAt least with acquisitions, Broadcom has a well-defined set of business metrics they expect from their companiesBroadcom acts somewhere like private equity in terms of investment, innovation, revenue generationIT'S A BOLD STRATEGY BROADCOM, LET’S SEE IF IT PAYS OFF FOR THEMIn essence, the bet is that there is no replacement for VMware in the EnterpriseThe timing is interesting with the shifting of budgets for AI projectsIt puts customers in a position to pay more for limited upside, but having to distinctly cut other areas of their technology budget (risk the business)Customers have some options, but again they risk the business (e.g. hold off on security patches)Once a company accepts the new pricing, what guarantees are there about no additional big increases in the future? How much will this impact the longer-term vendor-customer relationship?FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Sean Falconer (@seanfalconer, Head of Dev Relations @SkyflowAPI, Host @software_daily) talks about security and privacy of LLMs and how to prevent PII (personally identifiable information) from leaking outSHOW: 807CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Want to win a Tesla Cybertruck or $100,000? Enter the WS02 Choreo Code Challenge (before August 30th)WSO2 Choreo - Why build a platform? Just add developers insteadCloudZero provides immediate and ongoing savings with 100% visibility into your total cloud spendSHOW NOTES:SkyFlow (homepage)Partially Redacted PodcastSoftware Engineering DailyTopic 1 - Our topic for today is the security and privacy LLMs. What’s Sean’s origin story?Topic 2 - Let’s dig into LLM security and privacy. We see this concern a lot on the podcast and we’ve touched on it with various past shows, but we haven’t dug in deep. First, let’s frame the problem. What are we talking about when we talk about LLM security and privacy?Topic 3 - First, there is a fear that customer PII information might leak out. Second, company IP or confidential into might leak out related to products or offerings. We’ve seen examples of both to date. This could be exposed in the form of integration into a model (query it for the answer) or in the fine-tuning or RAG stage. Either one could lead to compliance issues, lost rev etc. But, that same data at risk is the potential differentiation of the models. How do you both mask the data but take advantage of the data?Topic 4 - One thing I’ve noticed is many orgs only think about privacy in relation to the fine-tuning stage where they are taking a broad model and making it company specific. It is about much more than that though. Just like standard software development, we have different stages. How is the data collected and stored, how is it used for training and fine-tuning, how is it used after deployment and during interaction stage, etc. How should security and privacy be handled across all phases?Topic 5 - Let’s talk beyond LLMs for a bit. What about Data Lakes and Data Warehousing? I see this as a problem across all big data, correct?Topic 6 - How does API security fit into this? Much of what we are talking about is at the storage and retrieval level. But, increasingly we see API issues exposing data. How does that fit in here?Topic 7 - Let’s talk podcasts, we had Jeff, the previous host of Software Engineering Daily on a few times. How are things over at Software Engineering Daily? Tell everyone a bit about the show.FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

If you’re planning to deploy AI for your business, here’s 5 important capabilities your business needs from the cloud era in order to be successful. SHOW: 806CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Want to win a Tesla Cybertruck or $100,000? Enter the WS02 Choreo Code Challenge (before April 30th)WSO2 Choreo - Why build a platform? Just add developers insteadSHOW NOTES:The Year Ahead in Cloud and Expectations for AI in 2024 (Altitude podcast)IF YOU WANT TO DO AI WELL, YOU NEED TO HAVE DONE CLOUD WELLWhen we first started doing cloud, the smart people would say, “If you don’t do IT well today, you won’t do cloud well in the future”.The same pattern will repeat itself with AI5 IMPORTANT CLOUD CAPABILITIES NEEDED TO SUCCEED WITH AIAutomate everything - Make automation mission-criticalBuild the right abstractions and flexibilities (e.g. sharing GPUs, Devtools, etc.)Leverage platforms to bring together Data Science, MLOps and AppDevKnow how much things cost (e.g. FinOps)Socialize success, and socialize learnings across teamsFEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod