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- Two copycat AI tools are under fire 🔥
Two copycat AI tools are under fire 🔥
Plus: NVIDIA just levelled up LLMs
Welcome back! Big news to kick us off today: Claude just got a major upgrade. Anthropic rolled out Claude 3.5 Sonnet yesterday. In short: It’s a beast.
The model is 2X as fast and 5X cheaper than before.
Plus, Claude 3.5 Sonnet excels at everything from visual reasoning to complex instructions.
In the race to AGI, Anthropic is making big moves. đź‘€
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Ethical Question Marks Surface With 2 New AI Tools
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Luma
Two new AI tools are making waves this week—but not just for their innovative tech. The rollout of Luma's Dream Machine filmmaking tool and AI-powered search engine Genspark are introducing new conversations about the ethics of borrowing tech, ideas, and inspiration. The question at the end of the day: What makes a copycat?
Here’s what you should know about the new tools…and controversy →
First up: Luma’s Dream Machine promises to revolutionize filmmaking by letting users create high-quality, realistic shots through simple text prompts. It’s trained directly on videos. But the ethical dilemma? It’s about transparency.
Luma’s trailer for its animated Monster Camp story featured a character that looks an awful lot like Mike Wazowski from Pixar’s Monsters, Inc.
This sparked questions about the video sources used to train the model—specifically, whether Dream Machine was trained on copyrighted material without permission.
Upon closer inspection, Mike from the actual Monster's Inc. Is in the cartoon. Straight up ripping it off.
— Jacob Davison (@JacobDavison_)
3:14 AM • Jun 16, 2024
Luma hasn't disclosed the datasets used for training, and Pixar owner Disney has stayed quiet (for now).
Next: We’ve got Genspark, an AI-powered search engine that creates custom summaries, or "Sparkpages," in response to user queries.
For example: If you type in “best baby formula for newborns,” Genspark gives you a comprehensive overview from various web sources.
Similar to fellow AI search engine Perplexity, Genspark aims to deliver high-quality results by using multiple specialized AI models.
The ethical dilemma here? Like Arc browser’s Arc Search and Google’s AI Overviews, Genspark’s use of AI to repurpose existing content without acknowledgment or approval has been criticized for not always giving proper credit to original content creators.
That’s nothing short of malicious content theft. Appalling behavior.
Better invest your loot well, boys, because the internet will remember and have no mercy down the road.
— Katie Berry 🤦🏻‍♀️ (@thatkatieberry)
10:55 PM • Jun 19, 2024
Why it matters: As AI tools become more advanced, the line between innovation and ethical irresponsibility gets blurrier.
The AI community (especially Anthropic with its research and Constitutional AI framework for deployment) is pushing for more transparency and fairness in developing these technologies, working toward a tech future where progress and ethics are given equal weight.
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NVIDIA Could Take LLM Performance to a New Level
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NVIDIA
NVIDIA's new tool could revolutionize LLM performance. Let’s break it down.
The who and what: AI and graphics processing powerhouse NVIDIA has announced Nemotron-4 340B, a family of open models designed to generate synthetic data for training large language models (LLMs) to be more accurate.
These models are set to transform industries like healthcare, finance, manufacturing, and retail by offering a scalable solution for generating high-quality training data.
The models include base, instruct, and reward versions that work together to create synthetic data.
The why: High-quality datasets are often expensive and hard to come by. Nemotron-4 340B tackles this issue by providing a free, scalable way to generate synthetic data, making it easier for companies to innovate without breaking the bank on data acquisition.
The how: Using NVIDIA’s NeMo framework, developers can customize the Nemotron-4 340B Base model for specific use cases, enhancing data quality and model performance.
These models are optimized for inference with NVIDIA TensorRT-LLM, which the company suggests can increase efficient performance at scale.
This setup allows developers to fine-tune their models pretty effortlessly.
Why it matters: By making robust datasets more accessible, tech like this empowers industries to develop more powerful and accurate AI models…for less $$$.
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Be the Next AI Innovator
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Join the 10 million people on Brilliant and start your 30-day free trial today. Plus, Future Tools readers get a special 20% off a premium annual subscription.
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Your New Customer Support AI
This week, Decagon stepped out of stealth with a shake-up to the AI-powered customer support scene.
The platform promises to mirror human capabilities and has already snagged big-name clients like Eventbrite, Bilt, Webflow, Rippling, and Substack. But enterprise solutions that promise human-like AI isn’t a new pitch.
So how is Decagon cutting through the noise to land these deals? Let’s get into it.
What sets Decagon apart: Unlike traditional chatbots, Decagon’s AI agents provide contextualized, conversational interactions throughout the entire customer support lifecycle. These agents can reason through complex business logic, take actions, improve from feedback, tag conversations, analyze trends, and even write new articles.
How it works: Decagon uses a mix of fine-tuned and third-party models to train its AI…like an organization’s knowledge bases and historical customer conversations, which give Decagon’s agents personalized responses.
Why it matters: Similar to TikTok’s new Symphony Digital Avatars, which use generative AI to create lifelike avatars for branded content, Decagon’s AI agents aim to replicate human-like interactions in customer support.
This human-like approach is quickly bridging the gap between scalable automation and personalized, genuine human engagement, thanks to AI.
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Google DeepMind debuts an AI that turns video pixels and text prompts into soundtracks.
Adobe Acrobat reinvents document creation with multi-format, AI-powered features.
OpenVLA launches as an open-source model enhancing generalist robotics capabilities.
Snap unveils advanced AI to push augmented reality to the next level.
Microsoft releases Florence-2, a versatile AI model for diverse vision tasks.
OpenAI’s former chief scientist launches a new AI venture.
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Ready to create your own AI-powered production studio? Watch as I dive into AI tools to whip up a music video (for free).
Is Elon Musk right about the Apple-OpenAI deal? On the latest episode of The Next Wave, we answer that very question. Don’t miss this one!
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That’s all for now! Looks like Claude is racing to get up to pace with ChatGPT—so keep an eye out for Anthropic. What do you think about the new model update? Give Claude 3.5 a whirl and hit reply with your thoughts!
—Matt (FutureTools.io)
P.S. This newsletter is 100% written by a human. Okay, maybe 96%.