A report from Knowledge at Wharton, noted that companies with a growth mindset generate more returns from AI investments. Wharton said 35% of companies measuring AI against growth outcomes report strong ROI compared to 13% measuring AI on efficiency alone.
Big banks reported third quarter earnings with a mixed bag of results. Here’s a look at the decks for Bank of America, JPMorgan Chase, Goldman Sachs and Morgan Stanley. BlackRock added for good measure. See: JPMorgan Chase aims to avoid AI lock-in, have nuanced view of AI agents
IBM said it is working with Siemens to develop IBM's nanostack architecture. The partnership combines IBM's semiconductor research and Siemens electronic design automation, process simulation, lithography optimization and manufacturing software.
Goldman Sachs reported strong third quarter earnings and CEO David Solomon provided his take on AI infrastructure and capital. He said:
"In our conversations with clients, demand for compute significantly exceeds supply at the moment, creating opportunities to help develop financing structures to meet that capacity shortfall. Our differentiated financing, distribution and investing capabilities position us to play a meaningful role in the mobilization of capital and supporting client activity. While we are proud of the privileged position we play in the AI investment cycle, no one knows how the demands for capital and compute will evolve as the broader AI ecosystem matures. That will only become clearer as technology and markets continue to develop.
This uncertainty reinforces the importance of remaining vigilant around the types of activity we finance and how we manage risk as we support our clients. We are highly selective about the risk we underwrite and the capital we commit, particularly as client financing needs become larger and more complex. Beyond these financial risks, we also recognize the broader concerns around the accelerating pace of AI technology and the unchecked advancement of frontier models.
Like other transformative technologies, AI presents significant opportunities, but also significant risks that must be carefully assessed and managed. However, the choice is not between halting progress and moving forward without guardrails. We must enable innovation and also demand responsibility."
Joe Marcella, VP planning and performance at Southwest, said it has had customers who bought seats for personal robots. The robot seats were often tied to events. After all, what conference doesn't have a personal robot as a prop these days. Marcella made the comments at IFS Unleashed 2026.
In a blog post, Google said Gemini 4 Argon is available for developers and enterprises. The company rolled out Gemini Argon 4 in the API in AI Studio and Gemini platform, Google AI Ultra subscribers, Google Antigravity, and Google AI Ultra and Pro subscribers. The model will also be in AI Mode in Search and the Gemini app.
An IBM Institute for Business Value has a few notable facts about consulting expectations in an AI-first world: "81% of executives say consulting services must change to remain relevant to their organization. Pricing is a top concern, with 68% of executives saying current delivery models are too costly and inefficient. As AI capabilities improve, business leaders expect more for less."
Anthropic said in a research blog that small AI models may be months away from self replicating on internet of things devices. Anthropic said:
"Our experiments suggest that small AI models may be months away from being capable enough to self-replicate on commercial internet-of-things (IoT) devices, like smart ovens and off-brand Android TV boxes. A replicator like this would be challenging to shut down, since there’s no centralized point to shut off—though it may be slow (with a doubling time of days). Unlike non-AI malware, it could also figure out unfamiliar devices on its own. In our evaluations, a 9B model got inference running on 8 of the 9 hardware types we tested."
Meta has released Muse Wonder and Muse Wonder Full in what it calls its most advanced models yet for personal and professional agentic AI tasks. Muse Wonder is available for developers and Muse Wonder Full is available for Muse Code subscribers. Muse Wonder will be the default model in Muse shortly.
Intel CEO Lip-Bu Tan and Broadcom CEO Hock Tan both said that capital could become the main constraint to the AI buildout. According to CNBC, Tan said capital is could become restrained due to interest rates and demand for returns. Go figure.
Amazon is reportedly in talks to buy Decart for $7 billion, according to the Wall Street Journal. Decart makes it easier to switch AI workloads between different processors. Combined with model routing, you can play this out where you'll route models as well as GPUs to optimize for cost. Given AWS has multiple instances and processors such as Trainium, Decart could be a good fit.
Microsoft CEO Satya Nadella talks about the need for deterministic controls for agentic AI systems and the conversation quickly turns to the great super intelligence sellout. Meanwhile, Marc Benioff said Agentforce will become SIForce on X. Note that Salesforce's web site hasn't changed so it's unclear whether the branding team knows yet. That's probably good because you could easily see SIForce as systems integration force. But I digress. My strategy with "super intelligence" goes like this:
