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🔗https://shre.ink/Wharton-GenAI-adoption-into-the-Enterprise

1. Context

The report arrives at a pivotal moment: After years of experimentation and hype around generative AI (Gen AI), enterprises are now moving into the deployment and value-capture phase.

The study’s authors note that organizations are no longer just testing tools—they are integrating Gen AI into core workflows, scaling up investment, tracking returns, and facing the real challenge of aligning people, processes and trust. In this sense, the report positions 2025 as the year of “accountable acceleration” rather than mere promise.

2. Study Objectives and Methodology

The core goals of the research were to take the pulse of enterprise Gen AI adoption—building on Wharton’s prior waves in 2023 and 2024—and to focus on usage, perception, investment, governance and human-capital dimensions.

🔗https://shre.ink/Google-Space-AI-Infrastructure

1. Introduction

Google frames AI as a foundational technology that will reshape many domains — science, business, society — and asks: where can we go to unlock its fullest potential?. Their answer: perhaps the best place to scale AI compute is space.

They point out that the Sun emits more power than 100 trillion times humanity’s total electricity production, and that in certain orbits a solar panel can receive up to eight times more annual energy than on Earth. With this in mind, their “moonshot” initiative, called Project Suncatcher, envisions constellations of solar-powered satellites, each carrying high-performance TPUs (Tensor Processing Units), connected by free-space optical links — in effect, a data-centre in orbit.

2. System design and key challenges

2.1 Achieving data centre-scale inter-satellite links

Cryptocurrency and AI: A Converging Future

Cryptocurrency and AI might seem like two worlds apart but increasingly they are converging. Companies that once focused solely on mining Bitcoin are now eyeing High-Performance Computing (HPC) and AI infrastructure as the next frontier for growth.

Take Bitfarms (NASDAQ: BITF) as a prime example. Known for powering Bitcoin transactions in Quebec, Canada, the company has pivoted to leverage its data centers, energy assets, and U.S. power campuses to provide HPC and AI infrastructure services. Essentially, Bitfarms is transforming its crypto mining assets into the computing backbone for AI, a market exploding in demand.

Why Crypto Players Are Jumping In

Crypto miners are natural candidates for AI infrastructure:

They already operate large scale data centers optimized for continuous high intensity workloads.

Control de Llamadas – La Clave para una Comunicación Eficiente

El control de llamadas (Call Control) es un componente esencial en los sistemas modernos de telecomunicaciones y redes empresariales. Su función principal consiste en gestionar el establecimiento, mantenimiento y finalización de las llamadas de voz y video entre usuarios o dispositivos. Este proceso no solo garantiza una comunicación fluida, sino que también optimiza el uso de los recursos de red, mejora la calidad del servicio y aumenta la productividad en entornos corporativos.

¿Qué es el Control de Llamadas?

El control de llamadas es el conjunto de protocolos, software y hardware que coordinan cómo se originan, dirigen, supervisan y terminan las llamadas dentro de una red. Este sistema se encarga de administrar el flujo de datos y las señales necesarias para establecer una conexión entre dos o más puntos.

En términos más simples, el control de llamadas decide quién puede hablar con…

🔗https://www.bain.com/insights/new-diligence-challenge-uncovering-ai-risks-and-opportunities/?utm_source=substack&utm_medium=email

1. Introduction

In today’s M&A and private equity world, assessing a target company means more than just looking at revenues and costs. The article argues that evaluating the impact of AI is now a core diligence task.

Buyers and investors are increasingly asking: How will AI reshuffle risk and opportunity in the business we’re about to acquire? This shift means that due diligence isn’t just checking boxes—it’s thinking about how the business model, cost structure and competitive dynamics might change because of AI.

2. What type of AI risk and opportunity do we see in diligence?

According to Bain, a key step is to map where the target sits in relation to AI’s impact. They define three categories:

🧩 Introduction

We are going to challenge one of the most repeated phrases of our time: “AI won’t take your job, but someone who knows how to use it will.”While it sounds motivational and partly true, the author argues that it’s dangerously simplistic.

AI doesn’t just automate tasks — it redesigns entire systems of work. That means even people who use AI might lose out if they don’t understand how it’s changing the structure of value.

To explain this, let us use a powerful historical analogy: the French Maginot Line, a perfect defense that turned out to be useless when the nature of warfare changed. The same thing is happening now: believing that learning to “use AI” is enough is like building a perfect defense for a war that’s already over.

⚙️ Lie #1: “If I learn to use AI, I’ll be safe”

This first lie assumes that jobs are…

🔗https://shre.ink/more-articles-created-by-AI-than-humas

1. Key Takeaways

Graphite’s study finds that at a point in late 2024 the volume of articles published on the open web that are AI-generated surpassed the volume of those written by humans. However, that growth has since plateaued rather than continuing to accelerate. A further disturbing but important nuance: while AI-written articles may now be more numerous, they are not proportionally visible in search engine results or AI tool citations—human-written content still dominates the top ranks. The study also flags that the statistics don’t account for AI-assisted human editing (where humans take AI drafts and heavily revise them) which may mean the real influence of AI is even larger.

2. Motivation

 The study notes many companies have adopted AI-content generation as a cost-efficient alternative to paying human writers, seeking to drive traffic via Google Search, social channels and answer-engines. Also, improvements in AI quality (sometimes matching or exceeding human-written text) and difficulty distinguishing…

Elon Musk’s artificial intelligence startup xAI has hired two former Nvidia researchers to accelerate the development of advanced “world models”—AI systems designed to understand and navigate real environments, beyond traditional text-based language models. This move positions xAI in direct competition with tech giants like Meta and Google in the race to create AI that can interact with and simulate the real world.

The company recruited Zeeshan Patel and Ethan He, both AI researchers experienced in world modeling during their tenure at Nvidia. According to reports from the Financial Times and confirmation from Patel’s personal website, he now works as a “Technical Staff Member at xAI focused on multimodal/world model research.” Nvidia has led in this field with its Omniverse platform, which creates and runs simulations for digital worlds.

World models represent a significant leap beyond current video generation systems like OpenAI’s Sora, which create content by predicting visual patterns from…

Where do we truly see the AI landscape evolving? Artificial intelligence has moved from research labs to the heart of business operations. Tools like ChatGPT or Copilot can write, summarize, and generate ideas but they are fundamentally processing engines, not automatic transformers of business.

The AI market is evolving. Large language models LLMs are volume driven, capital intensive products. They require massive computing power, huge datasets, and billions in investment, meaning this base layer will be dominated by a few players monetizing access through usage based pricing. These foundational models are essential but commoditized. The real differentiation comes higher up the pyramid, where AI is applied to solve industry specific problems.

Many companies start small using AI to automate routine tasks or slightly boost productivity. While useful, that is just the beginning. The true advantage comes when AI is embedded in core processes, enabling smarter decisions and measurable outcomes.

The financial…