The co-founder of a leading US artificial intelligence firm is making a comeback to the company that terminated him as CEO last week, the latest twist in a week-long drama over its leadership. OpenAI, which owns the popular chatbot ChatGPT, announced late on Tuesday on the social media platform X that it had reached "an agreement in principle" to bring back tech entrepreneur Sam Altman as CEO. We have reached an agreement in principle for Sam Altman to return to OpenAI as CEO with a new initial board of Bret Taylor (Chair), Larry Summers, and Adam D'Angelo. We are collaborating to figure out the details. Thank you so much for your patience through this.

For some, it is self-evident to use AI in their business and digitalization in the company. For others, it seems more like a trend. And yet we can observe how more and more AI platforms are in use. Nevertheless, and perhaps precisely because of this, it is challenging to determine how to implement this technology. If misused, misunderstood, or wrongly applied, artificial intelligence can damage businesses.

Adoption of deep learning has gained a lot of traction during the last two or three years across a wide variety of use cases and has become a top area of interest for many enterprises around the world. Yet, these enterprises still need to determine how best to spend their investment to yield meaningful results for their business. Once an organization has identified the most advantageous use case with which to begin, it is important for CIOs to consider a thoroughly deliberated architectural design. On the one hand, the toolchain for deep learning environments is diverse. There are a wide variety of development toolkits, frameworks and libraries from which to choose. Even the choice of hardware to run the deep learning workload can have a significant impact on an organization's results.

Leading brands around the globe are all using AI for digital marketing. As a result, marketing AI is now a flourishing market, with an ever-increasing number of use cases. Today, we share seven essential steps that every marketer needs to know before starting their AI journey. Artificial Intelligence (AI) is rapidly transforming every aspect of how we work. As data volumes steadily rise, AI allows digital marketers to fully utilize the potential of available data.

For almost all machine learning projects, the main steps of the ideal solution remains same. For each step, I was doing some research on the web depending on my business object and jotting down the best resources I ran across. The resources include Online Courses, Kernels from Kaggle, Cheat Sheets and Blog Posts. Below I've listed them and categorised by each step (all of the resources are free except the ones that have'paid' in the end):

Finance is something that no person on earth can live without. It is the basic necessity of life, as everybody needs money to eat, travel, and buy things. Although as technology gets smarter so do people. The present financial market is already comprised of humans as well as machines. People are finding more and more ways to default on loans, stealing money from others account, creating a fake credit rating etc. Today, machine learning plays an integral role in many phases of the financial ecosystem.

In the early 1990s, the general public made its earliest forays into using the Internet. At the time, no one could have imagined where the technology would lead. Social media, e-commerce, mobile apps, cloud computing, software as a service – the list is endless. Entire classes of applications – even industries – were not even a gleam in their creators' eyes. Today these internet-based technologies have transformed the way we live and work.