SAP Supercharging Development with New AI Tool 🔋🔌⚡
Plus: Cohere’s Advanced Text Embedding Model. Luma AI’s Genie Converts Text to 3D.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 139th edition of The AI Edge newsletter. This edition brings you SAP’s New AI Tool “SAP Build Code” For Developers.
And a huge shoutout to our incredible readers. We appreciate you😊
In today’s edition:
🔋 SAP Supercharging Development with New AI Tool
.📝Cohere’s Advanced Text Embedding Model
🧞 Luma AI’s Genie Converts Text to 3D
📚 Knowledge Nugget: How to Train an AI? by
Let’s go!
SAP Supercharging Development with New AI Tool
SAP is introducing SAP Build Code, an application development solution incorporating gen AI to streamline coding, testing, and managing Java and JavaScript application life cycles. This new offering includes pre-built integrations, APIs, and connectors, as well as guided templates and best practices to accelerate development.
SAP Build Code enables collaboration between developers and business experts, allowing for faster innovation. With the power of generative AI, developers can rapidly build business applications using code generation from natural language descriptions. SAP Build Code is tailored for SAP development, seamlessly connecting applications, data, and processes across SAP and non-SAP assets.
Why does this matter?
Build code aligns technical development with business needs and enables organizations to innovate and adapt more effectively in a competitive AI market. The evolution of application development, particularly in the context of the SAP ecosystem, can potentially change how businesses approach software development and innovation.
Cohere’s Advanced Text Embedding Model
Cohere recently Introduced Embed v3, the latest and most advanced embedding model by Cohere. It offers top-notch performance in matching queries to document topics and assessing content quality. Embed v3 can rank high-quality documents, making it useful for noisy datasets.
The model also includes a compression-aware training method, reducing costs for running vector databases. Developers can use Embed v3 to improve search applications and retrievals for RAG systems. It overcomes the limitations of generative models by connecting with company data and providing comprehensive summaries. Cohere is releasing new English and multilingual Embed versions with impressive performance on benchmarks.
Why does this matter?
In an age of vast and noisy datasets, having a model that can identify and prioritize valuable content is crucial. Also, the compression-aware training method is a practical advantage, It lowers operational costs by reducing the resources required to maintain vector databases. The availability of both English and multilingual versions opens up possibilities for international applications, breaking language barriers.
Luma AI’s Genie Converts Text to 3D
Luma AI has developed an AI tool called Genie that allows users to create realistic 3D models from text prompts. Genie is powered by a deep neural network that has been trained on a large dataset of 3D shapes, textures, and scenes.
🌟 Create 3D things in seconds on Discord
🎨 Prototype in various styles
✨ Customize materials
🆓 Free during research preview
It can learn the relationships between words and 3D objects and generate novel shapes that are consistent with the input.
Why does this matter?
This tool has the potential to democratize 3D content creation and make it accessible to anyone. Luma AI's co-founder and CEO, Amit Patel, believes all visual generative models should work in 3D to create plausible and useful content.
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Knowledge Nugget: How to Train an AI?
This comprehensive guide by
explores the process of training an AI model, covering topics such as algorithm selection, data collection, preprocessing, hyperparameter tuning, and ethical considerations. The choice of machine learning algorithms and neural networks is crucial in shaping the model's capabilities.High-quality data and effective preprocessing techniques are essential for accurate predictions. Hyperparameter tuning and strategies to combat overfitting refine the model's performance. Evaluative methods, including domain-specific metrics, provide quantitative assessments. Scalable architecture and computational efficiency are important considerations. Legal and ethical compliance is paramount. Specialized training approaches, such as fine-tuning and prompt-tuning, are emerging trends in the field.
Why does this matter?
A helpful guide for training AI models emphasizes the critical role of machine learning algorithms and neural networks in shaping model capabilities. It covers picking the right tools, using good data, and making the model work better. It also discusses checking how well the model does its job, using it on a bigger scale, and ensuring it follows the rules. It's a must-read for people learning about AI.
What Else Is Happening❗
🚀 Midjourney introduced a new feature, ‘Style-tuner’
For easier and more unified image generation, users can select from various styles and obtain a code to apply to all their works, keeping them in the same aesthetic family. Beneficial for enterprises and brands working on group creative projects. To use the style tuner, users simply type "/tune" followed by their prompt in the Midjourney Discord server. (Link)
🚀 Runway’s new update to its Gen-2 model with incredible AI video capabilities
The update includes major improvements to the fidelity and consistency of video results. Gen-2 allows users to generate new 4-second videos from text prompts or add motion to uploaded images. The update also introduces "Director Mode," which allows users to control the camera movement in their AI-generated videos. (Link)
🚀 Microsoft’s new survey on business value and opportunity of AI
The study surveyed over 2k business leaders and decision-makers and found that 71% of companies already use AI. | AI deployments typically take 12 months or less, and organizations see a return on their AI investments within 14 months. | For every $1 invested in AI, companies realize an average return of $3.5X. (Link)
🚀 Google AI’s new approach for adaptive LLM prompting
Researchers proposed a method called Consistency-Based Self-Adaptive Prompting (COSP) to select and construct pseudo-demonstrations for LLMs using unlabeled samples and the models' own predictions, closing the performance gap between zero-shot and few-shot setups. (Link)
🚀 Brave privacy-focused browser, has introduced new AI Leo
Which claims to offer unparalleled privacy compared to other chatbot services like Bing and ChatGPT. Leo can translate, answer questions, summarize web pages, and generate content. A premium version called Leo Premium is also available for $15 monthly, offering access to different AI language models and additional features. (Link)
That's all for now!
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