INDEPENDENT RESEARCH / PRACTICE NOTES
This is my working notebook on AI engineering, strategy, knowledge infrastructure, organizational transformation, and the human systems that determine whether innovation becomes real capability.
The notes range from emerging research questions to practical operating models. Some will become papers, tools, talks, or products. Others are here because thinking improves when it is made visible.
Meta and Microsoft have announced commercial access to Llama 2, with support across Azure and Windows. The release expands the range of models organizations can host, adapt, and integrate under their own architectural choices rather than consume only through a closed service.
That optionality is valuable. It also moves more of the responsibility from procurement into engineering.
Anthropic has released Claude 2 with a context window that can accept roughly 100,000 tokens—enough for hundreds of pages of material in one prompt. The immediate attraction is obvious: a user can bring a long report, technical documentation, or even a book into a conversation without dividing it into tiny fragments.
More context changes what a language model can see. It does not guarantee that the model will attend to the right thing.
OpenAI has made the Generative Pre-trained Transformer 4 (GPT-4) application programming interface generally available to existing paying developers and announced a retirement path for several older completion and embedding models. The two developments belong together. Production access is not only about opening capacity; it is about managing change.
When an external model becomes part of an application, version stability and migration become product concerns.
Microsoft has spent the spring adding generative artificial intelligence capabilities across Azure, developer tools, and business applications. In this month's platform update, one sentence deserves more attention than another feature list: generative AI does not absolve builders from thinking about what good product-making looks like.
That should be the operating principle for the current wave of experimentation.
The National Institute of Standards and Technology (NIST) has formed a public working group to help develop guidance for generative artificial intelligence. The group will begin by considering how the Artificial Intelligence Risk Management Framework (AI RMF) applies to these systems and will draw input from industry, academia, government, and civil society.
That open process is not a detour on the way to a standard. It is part of how a credible standard is made.
OpenAI has added function-calling support to its chat models. Developers can describe functions using structured definitions, and the model can return arguments that an application may use to call external tools or retrieve information.
This is an important improvement for building reliable integrations. It also makes a boundary explicit: the model proposes; the application decides what happens next.
The Defense Advanced Research Projects Agency (DARPA) has selected teams for its In the Moment program, which is exploring how machines might support difficult decisions when established rules are incomplete. Initial research focuses include mass-casualty triage and other settings where time, uncertainty, and competing values make judgment unusually demanding.
This is a serious test of human-centered artificial intelligence: not whether a model can produce an answer, but whether a human–machine team can make a better decision under pressure without obscuring who remains responsible.
International Business Machines (IBM) and ASM Pacific Technology (ASMPT) have announced progress in hybrid bonding, a packaging technique that can connect smaller chip components with far denser interconnections. The development is part of a broader move toward chiplets: modular components that can be combined into a larger system rather than fabricating every function on one monolithic chip.
The architectural promise is flexibility. The management challenge is that more of the system's performance and trust now lives at the interfaces among components and organizations.