When AI Challenges Strategy
How three chief strategy officers are responding
It is sometimes said that neural networks are “just” logistic regression. (Remember neural networks? LLMs are neural networks, but nobody talks about neural networks anymore.) In some sense a neural network is logistic regression with more parameters, a lot more parameters, but more is different. New phenomena emerge at scale that could not have been anticipated at a smaller scale. Logistic regression can work surprisingly well on small data sets. One of my clients filed a patent on a simple […]
I was working with a colleague recently on a project involving the use of the OpenAI API. I brought up the idea that, perhaps it is possible to improve the accuracy of API response by modifying the API call to increase the amount of reasoning performed. My colleague quickly asked ChatGPT if this was possible, and the answer came back “No, it’s not possible to do that.” then I asked essentially the same question to my own instance […]
Analog Ising machines have been proposed as heuristic hardware solvers for combinatorial optimization problems, with the potential to outperform conventional approaches, provided that their hyperparameters are carefully tuned. Their temporal evolution is often described using time-continuous dynamics. However, most experimental implementations rely on measurement-feedback architectures that operate in a time-discrete manner. We observe that in such setups, the range of effective hyperparameters is substantially smaller than in the envisioned time-continuous analog Ising machine. In this paper, we analyze […]
One of the quickest ways to call multiple AI models from a single Python script is to use OpenRouter’s API, which acts as a unified routing layer between your code and multiple AI providers. By the end of this guide, you’ll access models from several providers through one unified API, as shown in the image below: OpenRouter Unified API Running Multiple AI Models This convenience matters because the AI ecosystem is highly fragmented: each provider exposes its own […]
CollectivIQ looks to give users more accurate answers to their AI queries by showing them responses that pull information from ChatGPT, Gemini, Claude, Grok — and up to 10 other models — all at the same time.
Background: Regulatory frameworks such as the Belmont Report, the Common Rule, and the Declaration of Helsinki require informed consent to ensure participants understand a study’s purpose and can make voluntary decisions about their involvement. Regulations including the General Data Protection Regulation (Regulation (EU) 2016/679) further emphasise that consent must be freely given and revocable without disadvantage. Although informed consent forms (ICFs) are intended to be clear and accessible, they have become increasingly lengthy and complex. Large language models […]
Noisy labels in distributed datasets induce severe local overfitting and consequently compromise the global model in federated learning (FL). Most existing solutions rely on selecting clean devices or aligning with public clean datasets, rather than endowing the model itself with robustness. In this paper, we propose FedCova, a dependency-free federated covariance learning framework that eliminates such external reliances by enhancing the model’s intrinsic robustness via a new perspective on feature covariances. Specifically, FedCova encodes data into a discriminative […]
Hi, is there any update regarding summary rejects ? Deadline is March 4 AOE, and my paper status is still “Submitted” on chairingtool. Does anyone know by when they will be out ? submitted by /u/AddendumNo5533 [link] [comments]
How to turn constant disruption into an advantage.