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🤖 Google Launches GPT-4 Competitor

🤖 Google Launches GPT-4 Competitor

Plus: 🖼️ Meta Debuts AI Image Generator, 🛒 Self-Checkout Is A Shoplifter’s Dream

Photo by Nathana Rebouças on Unsplash

🤖 Google Launches Gemini—A Powerful AI Model It Says Can Surpass GPT-4

Google has launched Gemini, a multimodal AI model family, to compete with OpenAI’s GPT-4.

Available in three sizes Ultra, Pro, and Nano — Gemini handles various inputs like text, code, images, and audio, aiming for accurate problem-solving and advice-giving across domains.

Gemini, a successor to Google’s PaLM 2, surpasses current benchmarks for large language models. Its mid-level model is globally used in the Google Bard chatbot.

It excels in coding, outperforming GPT-4 on several machine learning benchmarks.

Google plans to roll out Gemini across various products, including Search, Ads, Chrome, and Duet AI. Developers and enterprise customers will also gain access through the Gemini API in Google AI Studio or Google Cloud Vertex AI from December 13 onwards.

🖼️ Meta Launches a Standalone AI-Powered Image Generator

Not to be outdone by Google’s Gemini launch, Meta’s rolling out Imagine with Meta.

Imagine with Meta is a new, standalone generative AI experience on the web, that allows users to create images by describing them in natural language.

Similar to OpenAI’s DALL-E, Midjourney, and Stable Diffusion, Imagine with Meta, creates high-resolution images from text prompts.

It’s free to use (at least for now) for users in the U.S. and generates four images per prompt.

The company plans to add watermarks to content generated by Imagine with Meta for increased transparency.

These invisible watermarks, resilient to common image manipulations, will be generated and detectable by an AI model.

🛒 Self-Checkout Machines Lead to 16 Times Higher Losses Than Cashiers

Shoplifters are 21 times more likely to steal from self-checkout than from cashier-operated lanes, that’s a 3.5% revenue loss.

Retail shrink, the fancy term for losses due to theft, costs U.S. retailers a staggering $100 billion a year.

The most common form of shoplifting is partial shrink, where a shopper pays for some items but “forgets” to pay for others.

To evaluate shrink rates, Grabango use computer vision to analyze nearly 5,000 retail transactions. The verdict? Self-checkout led to a shrink rate of more than 16 times higher than traditional cashier lines.

Checkout-free technology powered by computer vision could eliminate self-checkout shrink by accurately tracking what shoppers pick up and charging them the exact amount they owe.