Highlights💡 

OpenAI's function calling & the future of GPT [Link]

OpenAI's focus on building a cohesive ecosystem highlights a new vision for the future of artificial general intelligence. With function-calling, GPT isn't just getting better—it'll become a master at using other tools.

Sam Altman, CEO of OpenAI, has repeatedly stated that the company is not currently working on GPT-5. While this has come as a surprise to many, once you step back from the current AI hype cycle, it begins to make a bit more sense. Unlike many of their rivals, OpenAI already knows how to train state-of-the-art models that excel at natural language. This also makes them keenly aware of the many current limitations of large language models (LLMs), and intimately familiar with the scaling laws that govern them.

Rather than rushing to release GPT-5, they are instead focused on learning how to extract maximum benefit from these models and filling the gaps that need to be overcome to move closer to artificial general intelligence (AGI). To understand why they would take this approach, let me establish some context. Continue reading…

Related: Use OpenAI functions to write more functions for future calls.

PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360° [Project][Paper][GitHub]

PanoHead is a new GAN with state-of-the-art performance in recovering textured 3D models from a single image.

Synthesis and reconstruction of 3D human head has gained increasing interest in computer vision and computer graphics recently. Existing state-of-the-art 3D generative adversarial networks (GANs) for 3D human head synthesis are either limited to near-frontal views or hard to preserve 3D consistency in large view angles. We propose PanoHead, the first 3D-aware generative model that enables high-quality view-consistent image synthesis of full heads in 360° with diverse appearance and detailed geometry using only in-the-wild unstructured images for training. At its core, we lift up the representation power of recent 3D GANs and bridge the data alignment gap when training from in-the-wild images with widely distributed views. Specifically, we propose a novel two-stage self-adaptive image alignment for robust 3D GAN training. We further introduce a tri-grid neural volume representation that effectively addresses front-face and back-head feature entanglement rooted in the widely-adopted tri-plane formulation. Our method instills prior knowledge of 2D image segmentation in adversarial learning of 3D neural scene structures, enabling compositable head synthesis in diverse backgrounds.

The official source code for Drag Your GAN is finally released [GitHub], [Try here], [Paper]

Interactive Point-based Manipulation on the Generative Image Manifold

YouTube is getting AI-powered dubbing [Link]

YouTube is bringing in the team from Aloud, which was part of Google’s Area 120 incubator.

YouTube wants to make it easier to dub your videos in other languages by giving you some help with AI. The company announced Thursday at VidCon that it’s bringing over the team from Aloud, an AI-powered dubbing service from Google’s Area 120 incubator.

YouTube is already testing the tool with “hundreds” of creators, YouTube’s Amjad Hanif says in a statement to The Verge. And Hanif says that Aloud currently supports a “few” languages, with “more to come”; according to spokesperson Jessica Gibby, Aloud is currently available in English, Spanish, and Portuguese.

Tools & Links 🛠️

Empower Your AI Journey: Key Resources, Software, and Innovations

Unclassified 🌀 

• Morning Brew - Get smarter in 5 minutes (it's free) [Link]

• Fiverr - Find the right freelance service, right away [Link]

• WFH.Team - Work from anywhere in the world [Link]

• Add your link here ➜

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