As a result of generative AI, 64% of C-suite leaders plan to hire more

Good morning. It's Wednesday, June 28, and I’m excited to bring you the latest updates in the world of AI. Let's dive in!

Here are the highlights:

Story: Despite ‘doom and gloom’ reports, 64% of C-suite leaders plan to hire more as a result of generative AI

AI Tools: What you can learn from testing 5 of the top web-based video AI tools.

Resources: How to use LLMS in synthesizing training data?

AI-Generated Images: AI-generated images of an alien influencer visiting the planet Earth.

Tutorial: What is prompt engineering?

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STORIES

1. Despite ‘doom and gloom’ reports, 64% of C-suite leaders plan to hire more as a result of generative AI.

Generative AI tools, such as ChatGPT, are making headlines due to their potential to disrupt various industries and impact job markets. A recent report from Goldman Sachs suggests that up to 300 million jobs globally may be influenced by this emerging technology. Contrary to expectations, a new study conducted by work marketplace Upwork reveals that a majority of C-suite leaders, approximately 64%, have alternative strategies in mind. They plan to increase their workforce in response to the rise of generative AI, according to the study that surveyed 1,400 U.S. business leaders.

2. Snowflake-Nvidia partnership could make it easier to build generative AI applications.

Nvidia's VP of enterprise computing, Manuvir Das, believes that Snowflake serves as a valuable data storage platform for companies. By leveraging Nvidia GPUs and the NeMo framework, businesses can develop applications on top of Snowflake's data and build customized machine learning models using their unique datasets. This combination, especially when incorporating generative AI, results in a powerful synergy.

3. Generative AI and the Future of Data Engineering.

Generative AI has greatly enhanced the usefulness of large language models for everyday individuals. From creating drawings of imaginative scenarios to drafting emails or important messages, these models have made such tasks effortless. It is inevitable that generative AI will also disrupt the field of data in significant ways. This story presents predictions derived from discussions with a diverse range of data leaders, including those from Fortune 500 companies to startups.

4. 12 Best Large Language Models (LLMs) in 2023.

In the quest for cutting-edge large language models (LLMs), extensive efforts are being made by large corporations, small startups, and the open-source community. With the release of numerous LLMs, it begs the question: which ones are the most capable? To discover the answer, follow our curated list of the top proprietary and open-source LLMs in 2023.

5. Who Owns OpenAI?

OpenAI is privately owned by a consortium of investors, including Microsoft, Khosla Ventures, Reid Hoffman, and other undisclosed entities. The specific ownership structure has not been publicly disclosed, and some of the founders of OpenAI are among the company's investors.

AI TOOLS

Coding: 

Content Creation: Image Creator from Microsoft Bing.

Content Creation: What You Can Learn From Testing 5 of the Top Web-Based Video AI Tools. The video below goes over the five AI video creation tools including RunwayML Gen-2, Kaiber, Deep Nostalgia, Synthesia, and Unboring.

RESOURCES

Article: How to use LLMS in synthesizing training data?

Article: What Is a Generative AI Model?

Article: Leveraging AI and Machine Learning in Low-Code Platforms.

Tutorial: What is prompt engineering?

Prompt engineering involves the practice of crafting effective instructions or queries to language models, aiming to obtain desired and relevant outputs. It requires understanding the model's capabilities and limitations, refining prompts through experimentation, and leveraging techniques to elicit accurate and specific responses.

Prompt engineering, for engineers, refers to the process of crafting precise instructions or queries to optimize the outputs of language models. It involves understanding the model's capabilities and limitations, iterating on prompts, and using techniques to achieve desired results. Various programming languages can be used for prompt engineering, depending on the specific implementation and the language model being utilized. Common programming languages include Python, JavaScript, and others that have libraries or APIs for interacting with language models. The video below provides an in-depth overview of prompt engineering.

Source: Elvis Saravia.

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AI-GENERATED IMAGES

Ready for some fun? Here are a couple of AI-generated images of an alien influencer visiting the planet Earth. See a series of images at the source link provided below:

Source: Reddit.

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