AI Search Goes Multimodal
Greetings Cohere Community,
Get ready to experience search like never before!?
Imagine a pendulum swinging between two extremes: razor-sharp search accuracy and those delightful “aha!” moments of unexpected discovery. What if you could capture both — precision and serendipity — while simplifying AI search??
That’s exactly what we’re delivering with the launch of Cohere Multimodal Embed 3, and we can’t wait for you to dive in.
Discover multimodal AI search
Multimodal AI search is shaking up how businesses handle search and discovery. By blending the power of text and images, enterprises can now unlock a deeper understanding of user intent — and make every search more intuitive and impactful than ever.
By analyzing multiple modalities, you can:
The recipe for success
The formula for transforming enterprise search is simple:
From highly personalized recommendations to sophisticated diagnostics, multimodal embeddings used for AI search and retrieval can help reshape and optimize customer experiences, business operations, and deliver more insights faster.
Take retailers, for example. They're using multimodal AI to bring visual search to ecommerce, making the whole experience feel more natural and intuitive. McKinsey partner Louise Herring recently shared, “One exciting development I’ve seen is in luxury retail, where AI is revolutionizing the discovery and inspiration phases of the customer journey.” By blending different types of data, businesses can deliver smarter search results and recommendations — a competitive edge that’s only set to grow.
What’s there to think about???
As multimodal AI search moves into real-world enterprise applications, it’s important to consider several key factors. These include:
Consider choosing an AI provider that will collaborate with you and help tackle data challenges together. Our solutions architects and forward-deployment engineers are passionate about solving tough challenges and partnering with customers to make real progress. Got a complex problem? Don’t hesitate to reach out — we’re here to help you make it happen!
The versatility of multimodal AI search opens the door for many applications across multiple fields and industries. Trends, like feature extraction to recognize visual objects, shapes, colors, or textures combined with personalization and real-time data retrieval and analysis, are shaping how businesses use multimodal embeddings — and the future looks bright. It’s yet another example of AI helping us do things better.
For more, check out our latest articles or read on for this month’s highlights and upcoming events.
Product?
This month, we launched Multimodal Embed 3, a state-of-the-art AI search model for text and images. Try it for optimized retrieval with a fine-tuned Command R now with seamless integration with Weights & Biases. And if you need a refresh, take a look at our step-by-step guide on fine-tuning.
领英推荐
For Business
Check out our new comprehensive guide on Enterprise AI Security and learn how to securely deploy LLM-powered applications in private environments, complete with real-world attack scenarios and actionable steps to tackle common vulnerabilities. Download it today.?
Developers
Thinking of building AI agents? We have three new tutorials to get you started. While you are there, you’ll notice we have streamlined our APIs to help you switch between models faster, whether on the Cohere platform or in a private deployment. Have questions? Join our monthly office hours, Nov 18 at 1 p.m. ET on Cohere Discord.
Research
Cohere For AI launched Aya Expanse, a family of highly performant multilingual models that excel across 23 languages and outperform other leading open-weights models. Aya Expanse models are available for researchers and developers on the Cohere platform, Kaggle, and Hugging Face.
Company
Our generative model Command R+ excels at tasks businesses need and just got named one of the best inventions of 2024 by Time! Want to learn more about how to deploy it securely? Check out Cohere Co-Founder Ivan Zhang speaking with Machine Learning Street Talk. Watch the interview.
Upcoming events with Cohere?
For all upcoming events, explore cohere.com/events.?
Explore what's possible in the Cohere playground.
Transformation Engineer BrandNewDay: Granted UK patents and Greentech inventions that support the 2030 UN SDG objectives.
1 个月2. The P(O) Equation: A Unified Framework We propose the following formulation: P(O)=∏i=1nwi?Di?Ti?Fi?eλit?αi2?Ps(Xi)P(O) = \prod_{i=1}^{n} w_i \cdot D_i \cdot T_i \cdot F_i \cdot e^{\lambda_i t} \cdot \alpha_i^2 \cdot P_s(X_i) Where: P(O)P(O): Probability of an optimal outcome. wiw_i: Weighting factor (system importance measure). DiD_i: Data relevance (how well the data fits the system in question). TiT_i: Time delay factor (causality constraints). FiF_i: Fortuitous factor (accounts for unexpected but significant correlations). eλite^{\lambda_i t}: Chaos-dependent decay (Lyapunov exponent governing sensitivity to initial conditions). αi2\alpha_i^2: Probability density of the system (from quantum mechanics). Ps(Xi)P_s(X_i): Normalization factor ensuring dimensional consistency. Providing a dimensional analysis ensures consistency and robustness in the equation's application across different physical regimes. Future derivations should establish its relation to existing quantum field theories and general relativity.
Weaving AI into business. AI strategist and operator, creator and builder | Co-founder 0260.AI
4 个月Can’t believe more people don’t know about this. We’ve got clients with literally this use case alone that are paying outrageous prices for Dam systems that this takes care of without the pain of labelling
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4 个月Data annotation or ai trainer remote India freelance
Exciting stuff, CohereCohere! Multimodal AI search sounds like a game-changer for user experience and business insights. Can't wait to dive into the newsletter!
Exciting stuff, CohereCohere! Multimodal AI search sounds like a game-changer for user experience and business insights. Can't wait to dive into your newsletter!