AI Business with Fexingo: Artificial Intelligence Companies, Models, and Enterprise Adoption

Episode 80 of AI Business with Fexingo dives into the economics of inference—the real cost of running an AI model every time it responds. Lucas and Luna break down why inference cost per query has become the key metric for AI companies, from OpenAI to startups deploying small language models. They discuss the surprising numbers: how a single GPT-4 class query can cost a fraction of a cent at scale...

Episode 79 of AI Business with Fexingo dives into the emerging trend of AI companies directly acquiring or building their own power generation assets, from natural gas plants to small modular reactors. Lucas and Luna discuss why firms like Microsoft, Amazon, and OpenAI are moving beyond PPA contracts to own energy infrastructure, driven by surging compute demands and grid constraints. They break d...

With Anthropic's Mythos model under an export ban that has dragged into mid-2026, Asian AI startups are releasing their own 'Mythos-like' models to fill the void. In this episode, Lucas and Luna examine three specific startups — Tokyo's Kizuna AI, Seoul's Hanbit Intelligence, and Singapore's Merlion Labs — that have each released large language models trained on region-specific data and optimized...

In this episode of AI Business with Fexingo, Lucas and Luna explore how artificial intelligence companies are increasingly relying on synthetic data — artificially generated datasets — to train their models. They discuss why companies like Anthropic, OpenAI, and Meta are turning to this approach, touching on the release of Anthropic's Mythos model to over 100 US companies and agencies. The convers...

Episode 76 of AI Business with Fexingo: Lucas and Luna explore a surprising AI data strategy—buying game studios. With NVIDIA down 7.1% in five days and Super Micro plunging 14%, the chip narrative is shifting. But behind the scenes, leading AI labs are acquiring game development teams to generate synthetic visual data for training foundation models. Lucas breaks down the economics: a single AAA g...

Episode 75 of AI Business with Fexingo explores the emerging practice of 'agent stress-testing' — building simulated digital worlds to probe AI agents for dangerous behaviors before deployment. Lucas and Luna discuss Patronus AI's recent $50 million raise, the White House asking OpenAI to slow-roll a model release over safety concerns, and how companies like NVIDIA and Palantir are investing in ad...

A new wave of AI startups is specializing in inference optimization — making trained models run faster, cheaper, and more efficiently in production. Lucas and Luna dig into why giants like NVIDIA and AMD are paying attention, how DeductiveAI fits into the landscape, and what this means for the cost of deploying AI at scale. They reference NVIDIA's 7.5% five-day slide, AMD's 2.2% dip, and ARM's 20....

Episode 73 explores the surprising shift from training to inference in AI. Lucas and Luna discuss why Cerebras stock plunged 14% after earnings — and what that says about the market's changing priorities. They examine how inference-startup acquisitions like DeductiveAI fit into a broader trend where efficiency at deployment matters more than raw compute. Specific data points: NVIDIA down 2.8% in f...

As AI models grow more capable, companies like Google DeepMind and Microsoft are hiring cognitive scientists—researchers who study how humans think, learn, and make decisions. In this episode, Lucas and Luna explore why understanding human cognition is becoming a competitive advantage in AI. They discuss a recent paper from DeepMind that used cognitive science principles to improve reasoning in la...

Episode 71 of AI Business with Fexingo digs into a surprising trend: big AI companies like Microsoft and Meta are renegotiating or buying back cloud compute from providers like Azure and AWS. With Microsoft stock down 5.1% and Meta down 6.3% in the past week, the hosts explore how these firms are cutting costs by repurchasing reserved capacity or shifting to in-house clusters. Lucas explains the e...

Episode 70 of AI Business with Fexingo. Lucas and Luna dive into the emerging trend of AI companies buying back cloud compute capacity from their own customers—a practice pioneered by hyperscalers like Microsoft, Google, and Amazon. Lucas explains how heavy AI training loads create unused compute windows that firms now resell, and why startups like CoreWeave and Lambda are disrupting the model. Lu...

A quiet shift is happening in AI infrastructure: companies like Microsoft, Amazon, and Google are no longer the default home for AI workloads. Lucas and Luna examine the growing trend of AI firms renegotiating or even walking away from cloud commitments, driven by rising costs, margin pressure, and the lure of dedicated inference hardware. With NVIDIA's GPU supply loosening, firms are building the...

As governments worldwide push for data sovereignty, AI companies are racing to build data centers within national borders. This episode explores how Microsoft, Amazon, and others are partnering with countries like India, Saudi Arabia, and France to keep training data local. We look at the economics: a single sovereign data center can cost $1 billion, but helps AI firms navigate tightening regulati...

This episode of AI Business with Fexingo dives into the fast-growing trend of AI companies designing their own chips. Hosts Lucas and Luna explore why tech giants like Microsoft and Meta are moving beyond off-the-shelf GPUs from NVIDIA and AMD, and what this means for the broader supply chain. With ARM's stock surging 15.4% in the past week and Broadcom up 7.7%, we break down the strategic shift t...

Episode 66 of AI Business with Fexingo examines why major AI firms like Amazon, Microsoft, and Google are moving from leasing data center capacity to constructing their own facilities. With NVIDIA up 2.7% in the last five days and AMD climbing 5%, the demand for AI compute is straining existing infrastructure. Lucas and Luna discuss the economics of ownership versus leasing, the role of colocation...

In this episode of AI Business with Fexingo, Lucas and Luna dive into the growing trend of AI model makers acquiring inference startups. With the recent purchase of DeductiveAI by a major player, they explore why companies are betting on specialized inference hardware and software to cut costs and improve latency. Lucas breaks down the economics: training might get the headlines, but inference is...

Lucas and Luna explore the surprising shift toward smaller, more efficient language models in enterprise AI. With NVIDIA up 2.7% in the past five days but inference costs still a major concern, companies like Microsoft and Google are now prioritizing models that can run on edge devices. The hosts discuss how SLMs are reshaping deployment strategies, citing examples from healthcare and manufacturin...

This episode explores why major AI companies are shifting from renting cloud capacity to building their own data centers. Lucas breaks down the economics: the upfront cost of a 500-megawatt facility is around $4 billion, but ownership cuts per-query inference costs by 40-60% versus leasing from hyperscalers. Luna points out that this trend is reshaping the supply chain, with companies like NVIDIA...

In this episode of AI Business with Fexingo, Lucas and Luna explore the surprising intersection of artificial intelligence and nuclear fusion. As AI data centers face a looming energy crunch, major tech companies are signing power purchase agreements with fusion startups. We break down a recent TechCrunch report showing that every fusion startup with over $100 million in funding has a tech giant a...

In episode 61 of AI Business with Fexingo, Lucas and Luna unpack a surprising acquisition: Elastic just bought DeductiveAI for up to $85 million. DeductiveAI is an inference startup that makes models run faster and cheaper in production. Why would a search company — not an AI model maker — shell out for inference tech? The hosts trace the logic from Elastic's core business to the broader trend of...

In this episode, Lucas and Luna explore why the biggest AI companies are increasingly designing and manufacturing their own custom silicon. With Broadcom up 6.6% in five days on reports of new custom chip deals, and AMD gaining 4.3% on its MI400 series momentum, the hosts examine how vertical integration is reshaping the AI hardware supply chain. Lucas details why companies like Amazon, Alphabet,...

ARM Holdings jumped over 22% in the past five days, pushing its market cap past $400 billion and reigniting the debate about who really owns AI silicon. In this episode, Lucas and Luna unpack what the ARM surge means — not for day traders, but for anyone watching the AI infrastructure stack. They compare ARM's licensing model to NVIDIA's integrated approach, examine why AMD is also up nearly 5% wh...

In this episode of AI Business with Fexingo, Lucas and Luna explore a growing trend: AI model makers like OpenAI, Anthropic, and xAI are building their own search engines instead of relying on Google or Bing. They discuss how this vertical integration changes data access, training pipelines, and user experience. With reference to recent news showing only 16 percent of Americans believe AI will pos...

Lucas and Luna explore a striking shift in AI infrastructure strategy: major AI companies are now acquiring power plants directly rather than relying solely on the grid. With a single large language model training run consuming as much electricity as thousands of homes, firms like OpenAI and Anthropic are signing long-term power purchase agreements and even buying existing natural gas and renewabl...

AMD shares surged 14.9% in five days, but the AI industry's bottleneck is shifting from chip supply to electricity supply. Lucas and Luna explore how major AI companies are now signing long-term power purchase agreements with nuclear and renewable plants, locking in energy for training clusters that consume as much electricity as a small city. They discuss the numbers: a single training run can co...