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- 🚀 AI Roundup: OpenAI AGI Progress, Gemini 1.5 Robotics, Digital Avatars, and Top AI CRM Tools
🚀 AI Roundup: OpenAI AGI Progress, Gemini 1.5 Robotics, Digital Avatars, and Top AI CRM Tools
🤖 Protect Your Gen AI Chatbots
Welcome, AI enthusiasts.

In today’s Generative AI Newsletter:
Protect Your Gen AI Chatbots from Data Breaches
OpenAI's AGI Progress Scale
Gemini 1.5 Pro Enhances Robot Navigation Capabilities
🔍The Future of Digital Avatars is Here
🔍 Anole: An Open, Autoregressive and Native Multimodal Models for Interleaved Image-Text Generation
Top 5 AI CRM Tools
Protect Your Gen AI Chatbots from Data Breaches
Did you know chatbots can be compromised through natural language interactions?
Attackers can jailbreak models & inject harmful prompts, extracting sensitive data.
This leads to financial losses, legal issues, and reputational damage.
Secure your AI to prevent these threats.
Tumeryk introduces the first Gen AI Security Studio, designed for multi-modal testing with NVIDIA Nemo Guardrails, ensuring your Gen AI applications' resilience.
Test for hallucinations with the Align Score
Real-time protection for OWASP risks for LLM & Gen AI models, including jailbreak prevention
Automate LLM Vulnerability Scanning
Implement Role-Based Access Control for LLMs
Conduct multimodal environment prompt testing
Tumeryk’s LLM Scanner generates comprehensive vulnerability reports and fortifies your AI models.

Reuters
OpenAI's AGI Progress Scale
OpenAI has created a five-level scale to measure its AI systems' advancement towards artificial general intelligence (AGI):
Level 1: Current conversational AI like ChatGPT.
Level 2: AI solving problems at a PhD level. OpenAI is close to this.
Level 3: AI performing actions for users.
Level 4: AI creating new innovations.
Level 5: AI handling tasks of entire organizations, representing AGI.
AGI is defined as a system surpassing humans in most valuable tasks.
This scale helps OpenAI track progress and support aligned projects. Despite advancements, AGI is estimated to be about five years away, according to CEO Sam Altman.
This scale's introduction follows OpenAI's partnership with Los Alamos National Laboratory to explore AI's role in scientific research, aiming to develop a safety-focused evaluation framework.
OpenAI has not detailed its categorization methodology.

Researchers are enhancing robots with large language models (LLMs) like Google DeepMind's Gemini, significantly improving their ability to perform real-world tasks and interact naturally with humans.
In California, a robot using Gemini processes text and video to navigate and execute commands, demonstrating high reliability even with complex instructions.
This integration represents a major leap in practical applications for LLMs beyond web browsers and apps, with industry and academic labs rapidly advancing AI-enhanced robotics.
The ease of training robots in real-world environments suggests a future where AI-enhanced robots become commonplace.

The Future of Digital Avatars is Here!
RodinHD revolutionizes digital avatars by retaining fine details like hair strands and textures, avoiding the "toy-like" appearance.
Key innovations include:
task replay for data scheduling, preventing catastrophic forgetting and maintaining detail fidelity
weight consolidation regularization to preserve sharp details and knowledge from previous training
enhanced portrait guidance using cross-attention for richer texture cues
optimized noise schedule, enabling high-detail 3D avatars from varied portrait inputs
RodinHD sets a new standard for realistic digital avatars.

🔍 Anole: An Open, Autoregressive and Native Multimodal Models for Interleaved Image-Text Generation
3 days ago, the Generative AI Research Lab (GAIR) introduced ANOLE: a groundbreaking model that's revolutionizing multimodal AI.
By fine-tuning Meta AI’s Chameleon, ANOLE was created – an open, autoregressive, native large multimodal model excelling in interleaved image-text generation.
🔍 The Challenge: Current multimodal models often rely on separate diffusion models for visual generation or lack native integration. This creates inefficiencies and limitations in generating truly seamless content.
Why ANOLE Stands Out:
Efficiency: Fine-tunes fewer than 40M parameters with just 6,000 samples.
Quality: Generates high-quality, coherent content that meets detailed instructions.
Accessibility: Open-sourced model, training framework, and instructional data to democratize advanced multimodal AI.
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Top 5 AI CRM Tools
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