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Sam, Jony, McGuffin and Vaporware
Is it ever a good time for a company to announce vaporware? Let’s discuss the pros and cons of pre-announcements, vaporware, and the strategy of products that may or may not ever exist. SHOW: 928SHOW TRANSCRIPT: The Cloudcast #928 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[US CLOUD] Cut Enterprise IT Support Costs by 30-50% with US Cloud[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.SHOW NOTES:The McGuffin “Challenge” - Software Defined Talk (May 30, 2025)McGuffin (Wikipedia)IS IT EVER A GOOD TIME TO PRE-ANNOUNCE SOMETHING? OR VAPORWARE ON PURPOSE?Russ Hanneman (Silicon Valley) - “No Revenue”Set a big ambition for the companyDistract the market from current company challengesDistract your competitors to chase something where they don’t have strengthsProbe the market for ideas - sort of like a “leak”Get the market to pump your valuation, so you can take other actionsStall your customers from potentially buying a competitive offerFEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod
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29:32
Preventing AI Hallucinations
Anand Kannappan (@anandnk24, CEO @PatronusAI) talks about evaluating AI models for hallucinations, managing data quality, automating the process, and optimizing models. SHOW: 927SHOW TRANSCRIPT: The Cloudcast #927 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" SPONSORS:[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.[US CLOUD] Cut Enterprise IT Support Costs by 30-50% with US CloudSHOW NOTES:Patronus AI websiteTopic 1 - Welcome to the show, Anand. Give everyone a quick introduction.Topic 2 - Our topic today is Preventing AI Model Hallucinations. Before we dig into that, I wanted to ask about your time as Lead Data Scientist at Meta. What was it like to be early into that organization, and what did you take away from your time there? Topic 3 - Ok, let’s dig into model evaluations and hallucinations. Let’s start at the beginning. How do model hallucinations come about?Topic 4 - When evaluating models for hallucinations, how does a developer or a data scientist know fact from fiction? Due to its size, complexity, and number of parameters, it’s not feasible to simply fact-check and manually verify inputs to outputs. How is this process evaluated and automated with some level of confidence? Additionally, numerous benchmarks are available. What are your thoughts on the usefulness of the benchmarks?Topic 5 - How does the concept of data quality play into this? How would we know when a model was given insufficient or improper data vs. a hallucinationTopic 6 - We often hear about how frontier models are running out of training data, and increasingly, synthetic data is being used. Does this impact hallucinations in any way?Topic 7 - The last item I wanted to ask you about, Partonus AI, also pertains to model optimization. Can you explain that process?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod
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27:51
AI and the 95% vs 5% debate
The industry is debating whether AI should be viewed as augmenting or replacing human-centric tasks. But we don’t yet have a framework to discuss the technical and business impacts of that spectrum of decisions. SHOW: 926SHOW TRANSCRIPT: The Cloudcast #926 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[US CLOUD] Cut Enterprise IT Support Costs by 30-50% with US Cloud[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.SHOW NOTES:The final 5% of AI successHOW DO WE THINK ABOUT THE INVOLVEMENT OF HUMANS WITH AI SYSTEMS?What do we think AI systems should be capable of?What do we think human systems should be capable of?We know how to quantify error, but do we really know how to quantify error?Almost every question about AI comes down to augment vs. replace, and yet humans tend to skew towards the replace angle. We like the thought of humans in the loop, but often don’t want to be bothered to interact with humansWe haven’t yet created a framework to think about the human +/- AI involvement, because we haven’t really created it for general-purpose automation yet either. FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod
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29:08
Universal Data Representation for AI
Joel Christner, (@joelchristner, Founder/CEO at @viewyourdata) discusses the complexities of data management in AI, structured and unstructured data, the importance of RAG pipelines and vector databases. SHOW SUMMARY: Aaron and Joel discusses the complexities of data management in AI, focusing on the concept of universal data representation. They explore the challenges organizations face with structured and unstructured data, the importance of RAG pipelines and vector databases, and the implications of data privacy in regulated industries. The conversation also touches on managing model versions and the emerging patterns in AI tooling that can help enterprises effectively utilize AI technologies.SHOW: 925SHOW TRANSCRIPT: The Cloudcast #925 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.[US CLOUD] Cut Enterprise IT Support Costs by 30-50% with US CloudSHOW NOTES:View.io websiteTopic 1 - Welcome to the show, Joel. Give everyone a quick introduction.Topic 2 - Our topic today is everything data and how to represent it and embed it into AI systems. First, what is the challenge with data, structured or unstructured, in organizations today and what is behind the concept of Universal Data RepresentationTopic 3 - Industry or customer specific data today is big challenge for organziations, especially in highly regulated industries such as healthcare, financial services, etc. The most prevalent solution I am seeing is taking an existing foundational model and then adding a RAG pipeline vs. the cost and time to fine tuning. What are you seeing?Topic 4 - Even when companies have good data, that doesn’t mean that data makes it into the AI pipeline correctly, this is where the embedding problem and your concept of Universal Data Representation comes into play, correct?Topic 5 - But, once you get the first model out, then what? How should the data and models be handled over time? How do you create a platform and a continuous feedback loop to improve the results over time?Topic 6 - What are the most successful use cases you are seeing today with your customers?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod
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28:13
Where do Developer-Assistants go next with AI?
Where does the next phase of AI-assistants for software development go next? Is it an evolution of developer productivity, or a complete rethinking of the barriers and limitations for broader software development? SHOW: 924SHOW TRANSCRIPT: The Cloudcast #924 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:Cut Enterprise IT Support Costs by 30-50% with US CloudSHOW NOTES:WHERE DO AI DEVELOPER-ASSISTANTS GO NEXT?A year ago it felt like co-pilots were one of the entry point use-cases for AI.Since then we’ve seen numbers say the uplift is 10-20% productivity.Microsoft claims that 20-30% of their code is now written by AIs.We’ve seen many senior developers speakout that it’s not replacement level technology and they don’t trust it.Companies like Cursor have a $9-10B valuation. Windsurf just got purchased for $3B by OpenAI.Microsoft has Co-Pilot (based on OpenAI models). Google and Amazon are rumored to be launching their own.Lots of companies are launching agents (IBM, Salesforce, Oracle, etc.), and lots of agent frameworks now exist. So where does it go next? Is it just wide-spead adoption of developer productivity? Is it specialized functions within developer workflows? (e.g. CI/CD, documentation, security evaluations, bug fixes, long-term maintenance, etc.)How far are we from teams being just a few architects, leads, Sr. Devs, and then teams of AI’s (agents, etc.)?Is that a good thing for Sr. Dev personalities that didn’t want to focus on soft-skills?Does that allow for greater experimentation against feature-requests or stories, since they can create more, test more, etc.?Do we start to see companies create skunkworks teams/groups that try to adopt this approach? Are product managers ready to have zero-backlogs and the demand for new ideas to increase?FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod
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25:17