OpenAI introduces DALL-E image editor

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OPEN-AI INTRODUCES DALL-E IMAGE EDITOR 🤯

Finally, I can edit my French fry pictures with ease! 🍟

What’s new? OpenAI’s DALL-E tool, capable of generating images from textual descriptions, now offers an intuitive editing interface.

How does it work? Accessible through a simple click on any image generated by DALL-E, this interface combines simplicity with sophistication. Users, on both desktop and through the mobile app, can either use the selection tool to highlight specific areas for editing or leverage conversational prompts directly in the interface, allowing users to describe desired changes naturally, without intricate selections. This makes for a more seamless image generation experience and reduces the need to reformulate prompts over and over until you get your desired result.

Why is this important? Allowing users to edit generated images directly on the DALL-E interface is a huge step forward for ChatGPT-powered image generation. However, similar features have been available for months now on Midjourney, a platform that still seems to lead the way in image generation. This is one of the few features within AI where OpenAI seems to be playing from behind.

APPLE INTRODUCES REALM, FASTER THAN GPT-4 🦾

Q: How do you make an apple turnover?

A: Roll it down a hill. 🍏

What’s new? Apple researchers have unveiled ReALM (Reference Resolution as Language Modeling), an AI system that understands on-screen information.

How does it work? What sets ReALM apart is its ability to tackle reference resolution in ways previous models have not been able to. This process involves deciphering ambiguous references to on-screen entities and grasping conversational nuances and contextual cues. Through textual representations, ReALM reconstructs the visual layout of screens, enhancing its understanding of on-screen entities and their locations. This allows the AI to “see” what the user sees on their screen.

Why is this important? Traditionally, reference resolution has posed a significant challenge for digital assistants, hindering their ability to understand indirect references and visual context. ReALM addresses this by treating reference resolution as a language modeling problem, effectively decoding visual elements displayed on screens. By mastering reference resolution, ReALM paves the way for more intuitive interactions with devices.

DATABRICKS’ NEW LLM FOR ENTERPRISES 🤓

Q: What did the bricklayer say to his wife on their wedding day?

A: It’s cement to be. 🧱

What’s new? Microsoft-backed company Databricks, known for their proficient analytics platform, has made a significant move into the world of Large Language Models (LLMs) with its open-source release of DBRX.

What sets DBRX apart? With a foundational model boasting 132 billion parameters, DBRX promises to revolutionize language understanding, programming, and mathematical operations for enterprises. Notably, Databricks has set DBRX apart by making it freely available on GitHub and Hugging Face, aiming to catalyze innovation across various industries. By empowering enterprises to build upon DBRX, Databricks aims to address concerns surrounding third-party ownership and governance, offering a pathway for organizations to deploy tailored LLM solutions efficiently.

“WATCH THIS” WEDNESDAY 👀

Our FryAI team sat down with tech expert Justice Conder to get his insights on the exciting possibilities and challenges that lie ahead in the world of AI. Check out our discussion below! 👇

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