Lucas and Luna explore the surprising trend of rapidly declining AI inference costs, using live data from June 2026 to show how companies like Snowflake and ServiceNow are benefiting. They discuss why this challenges the prevailing 'AI will be expensive' narrative and what it means for startups and enterprise adoption.

#AI #InferenceCosts #LargeLanguageModels #GenerativeAI #Snowflake #ServiceNow #Technology #Business #FexingoBusiness #BusinessPodcast #AIEconomics #CloudComputing #Startups #EnterpriseAI #CostTrends #ModelDeployment #DataDriven #June2026

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Lucas and Luna unpack an overlooked structural shift in the AI economy: the way model training is starting to mimic the capital-intensive, cyclical dynamics of the oil industry. Using the recent 48 percent surge in Snowflake stock as a hook, they explore how data scarcity, compute hoarding, and inference costs are creating a new class of 'AI reserves.' With NVIDIA dipping and AMD soaring, they ask whether the market is pricing in a supply glut or a permanent scarcity premium. A conversation about the strange economics of artificial intelligence — and why the next bottleneck isn't chips, it's clean data.

#AI #TokenEconomics #Snowflake #NVIDIA #AMD #DataScarcity #InferenceCosts #ComputeHoarding #AIReserves #Technology #FexingoBusiness #BusinessPodcast #TechPodcast #GenerativeAI #LargeLanguageModels #DataCenters #MachineLearning #AIInfrastructure

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Lucas and Luna dig into the latest data on AI inference costs — which are falling even faster than training costs. They explore how the shift from training to inference is reshaping the economics of AI deployment, from startups to hyperscalers. With real numbers from Snowflake, ServiceNow, and AMD's recent surge, they explain why inference is becoming the new battleground for cloud providers and chip makers. Plus, they discuss what 'inference at scale' means for developers and enterprises in 2026.

#AI #Inference #LLM #CostCrash #Snowflake #ServiceNow #AMD #NVIDIA #CloudComputing #MachineLearning #GenerativeAI #FexingoBusiness #BusinessPodcast #Technology #AIEconomics #ChipDesign #EnterpriseAI #ModelDeployment

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Lucas and Luna unpack the surprising economics of AI inference — why running models is getting dramatically cheaper while training costs stay high. With Snowflake up 48% in a week and ServiceNow up 22%, the hosts connect the dots between infrastructure demand and stock moves. They explore how model distillation, hardware specialization, and cloud competition are driving inference costs down 90% year-over-year, and what that means for developers and enterprise buyers. A specific look at one overlooked number that changes the AI investment thesis.

#AIInference #AIEconomics #Snowflake #ServiceNow #ModelDistillation #Cerebras #Groq #CloudCompetition #InfrastructureAsCode #FexingoBusiness #BusinessPodcast #Technology #AIHardware #CostCrash #OpenSourceAI #InferenceCosts #DeveloperTools #AIMonetization

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GitHub Copilot just switched to token-based billing and developers are furious. Lucas and Luna break down exactly what changed, why tokens are such a different pricing model from the old flat fee, and what it reveals about the economics of AI coding tools. They also look at how rival tools like Amazon CodeWhisperer and Cursor are positioning themselves in this moment. Plus: a $50 million monthly bill for one large enterprise using Copilot? If that number makes you wince, you will want to hear how the math works.

#GitHubCopilot #TokenBilling #AIProgramming #DeveloperTools #Microsoft #GenerativeAI #LLM #Pricing #SoftwareDevelopment #AmazonCodeWhisperer #Cursor #TechEconomics #AIAdoption #EnterpriseSoftware #Technology #FexingoBusiness #BusinessPodcast #ChatGPTAndBeyond

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Lucas and Luna explore the surprising economics behind fine-tuning large language models, using live market data to show how companies like Palantir, Snowflake, and ServiceNow are betting on custom models. They discuss the cost of fine-tuning vs. building from scratch, the rise of parameter-efficient methods, and what this means for enterprise AI adoption. Based on May 30, 2026 market moves, they connect Palantir's 14% weekly gain and Snowflake's 48% surge to demand for adaptable AI systems. A concrete look at how fine-tuning is reshaping the AI value chain.

#AI #FineTuning #LLM #EnterpriseAI #Palantir #Snowflake #ServiceNow #MachineLearning #DeepLearning #Technology #BusinessPodcast #FexingoBusiness #Podcast #GenerativeAI #ModelTraining #CostEconomics #AIAdoption #DataScience

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Lucas and Luna dig into the latest breakthrough in artificial intelligence: chain-of-thought reasoning and planning capabilities in large language models. They explore how models like OpenAI's o3 and DeepSeek-R1 are moving beyond pattern matching to deliberate problem-solving, using real examples from math competitions and coding challenges. The hosts discuss the implications for enterprise software, referencing recent gains in stocks like ServiceNow (up 20.9% in a week) and Snowflake (up 47.3%), and examine why this shift matters for productivity tools. Lucas explains how chain-of-thought works, why it's different from previous approaches, and what it means for jobs that require complex decision-making. Luna questions whether this is true reasoning or just better mimicry. The episode also touches on the energy cost of these deeper reasoning models and how companies like Groq are building chips optimized for inference. A concrete, accessible look at one of the most important AI developments of 2026.

#ChainOfThought #Reasoning #LLMs #AIProductivity #OpenAI #DeepSeek #ServiceNow #Snowflake #Groq #Inference #Planning #EnterpriseAI #Technology #AIJobs #FexingoBusiness #BusinessPodcast #GenerativeAI #MachineLearning

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Lucas and Luna explore how AI is driving a fundamental shift in web architecture: more and more web content is being designed for machine consumption, not human eyeballs. They discuss Google's structured data boom, the rise of API-first content platforms, and how this transformation affects SEO, web development, and user experience. With data showing Snowflake up 44.5% in a week and a TechCrunch headline about the internet being rebuilt for machines, the episode dives into what this means for businesses and everyday users. Specific examples include schema markup proliferation, AI-generated content pipelines, and the tension between human-friendly design and machine-readable efficiency.

#InternetForMachines #AIWeb #StructuredData #SEO #APIFirst #TechCrunch #Snowflake #WebArchitecture #MachineReadable #GenerativeAI #GoogleSearch #WebDevelopment #ContentPipelines #FexingoBusiness #TechnologyPodcast #ChatGPTandBeyond #LucasAndLuna #BusinessPodcast

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Lucas and Luna explore how AI agents are evolving from simple chatbots to autonomous workflow managers. They discuss Salesforce's Agentforce, Microsoft's Copilot expansions, and the economic shift toward outcome-based pricing. The hosts also analyze how Snowflake's recent 44.9 percent surge ties into the growing demand for data infrastructure that powers these agents. Along the way, they touch on the security implications and the new job roles emerging to manage agent teams. With real-world examples and concrete numbers, they cut through the hype to show what actually works in 2026.

#AIWorkflow #AgenticAI #SalesforceAgentforce #MicrosoftCopilot #Snowflake #AIProductivity #EnterpriseAI #OutcomeBasedPricing #AISecurity #AIJobs #Technology #FexingoBusiness #BusinessPodcast #Podcast #TechPodcast #AI #WorkflowAutomation #DataInfrastructure

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In this episode of ChatGPT and Beyond with Fexingo, Lucas and Luna explore why large language models like GPT-4o and Google's Gemini struggle with basic spelling—even as they ace complex coding tasks. They unpack a recent viral headline about AI's inability to spell 'Google' and trace it to the fundamental architecture of tokenization. The conversation touches on Google's tokenizer, the Byte-Pair Encoding algorithm, and the ironic trade-off: models that can't spell outperform humans on coding benchmarks. Lucas connects it to a broader pattern in AI development—small models that sidestep these issues, and what it means for enterprise tools. Grounded in real market data (NVDA, AMD, SMCI) and a TechCrunch report from May 28, 2026, this episode gives listeners a concrete lens into how AI actually 'thinks' in letters.

#LargeLanguageModels #GenerativeAI #Tokenization #SpellingAI #GoogleAI #GPT4o #Gemini #BytePairEncoding #TechCrunch #NVIDIA #AMD #SuperMicro #AICoding #EnterpriseAI #Technology #FexingoBusiness #BusinessPodcast #AIProductivity

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