PRODUCTS

Why Claude's workplace play threatens incumbents

Anthropic is looking at more ways to broaden its enterprise lead by targeting productivity tools. 

On Tuesday, Anthropic announced a new suite of Claude tools, including Meetings, Whiteboards, Sheets and Data, and more powerful interactive connectors. These join Anthropic's existing tools, such as Docs, Slides, Design, and Motion, which the company says have helped people create more than 45 million docs, decks, and designs. 

The Claude ecosystem is becoming so expansive that it rivals those from Google or Microsoft, creating proprietary solutions for a large array of workplace tasks that integrate the context and assets that organizations have shared with the model. 

"For years, we've learned to work around software. Now Claude works around you," said Ami Vora, chief product officer at Anthropic.

The standout offering of the new suite is Claude Meetings, which lets Claude join video calls as a visible participant, like Otter.ai or Fireflies.ai. Claude Meetings, however, goes a step further than these competitors, moving from notes and conversations about the meeting to action, such as laying out a timeline on a whiteboard, or using the work apps people have already connected to pull up last year's numbers. At launch, it will be available in beta on Team and Enterprise plans. 

The other new tools are more catered to specific areas of knowledge work:

• Claude Whiteboards: a shared board a team can work on with Claude, available in beta on paid plans. 

• Claude Sheets: a spreadsheet that Claude builds and edits with a team, available in beta on paid plans. 

• Claude Data: formerly known as Claude Dashboards, helps connect Claude to companies' data repositories, such as a data warehouse or CRM. It is now generally available on all paid plans. 

Anthropic also launched interactive connectors to all plans, including free users. With this, users can link Claude to the apps they already use, giving Claude the information it needs and enabling it to take action from there. If this sounds familiar, it's because interactive connectors have been tested since January, showing a small live view of certain apps in Claude chats. Now, Claude can launch full apps within its interface that look like they would on a partner site.

Ultimately, this update delivers one big win: eliminating context switching for users. Even though working professionals may be used to using one software for most of their careers, they may be incentivized to switch if they already rely on Claude as their primary AI chatbot or assistant. For instance, even if you're a Microsoft Excel user, you may want to start by using Claude Sheets to edit and create spreadsheets. Because you can still export work as Excel files, you don't compromise the compatibility. Rather, you just optimize the creation process. While competitors like Google and Microsoft already have AI assistants within tools employees already know, at this point, apps like Claude are well-established in many employee workflows, earning them a great deal of user trust and context. With AI, you're most likely to keep using the tool you are most familiar with, not only because you know how to talk to it, but because what it has learned from you helps you get the answers you need faster. 

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TOGETHER WITH GRANOLA

Our favourite AI notepad can now type for you

Our team already uses Granola to take notes in meetings. Now it can do the typing between them, too.

Our favourite use case for Voice Typing so far: AI prompts.

Instead of typing out a long prompt, press a hotkey and basically brain-dump everything you’re thinking. We’ve found it much easier to get all the context, ideas, and details out quickly, which gives the AI more to work with. That greatly improves the results and value you can get from your AI.

Other Voice Typing use cases we’ve found helpful:

• Voice type longer emails and messages

• Fire off Slack replies in quick succession

• Get thoughts or ideas down in notes quickly without stopping to type.

And because Granola already knows the names and jargon from your meetings, it has context for the way you and your team actually talk. Across our team, we haven’t had to correct a single word it’s transcribed yet, despite a few funky accents.

Try Granola Voice Typing, with unlimited words

RESEARCH

Can AI agents solve robotics' reliability gap?

Agents have been the hottest buzzword in AI this year. New tools from UC Berkeley and Nvidia may bring them to the physical world. 

On Monday, the university announced new open-source research and benchmarks for "agentic robotics," an approach that brings agents into designing, testing and refining robotics systems for industrial tasks. UC Berkeley researchers designed this with Nvidia Isaac, the company's robotics simulation and synthetic data generation platform, allowing builders to develop robotics with less data. 

The release includes two main components: 

• Graph-as-Policy, or GaP, is a framework that lets agents generate, connect and test skills for robots to complete tasks. For instance, the system will segment skills such as finding an object, planning a grasp and moving the gripper without collisions into individual parts. The agent then connects these skills and uses Nvidia Isaac to simulate and rehearse them. 

• VABAR, or Variational Automation Benchmark for Agentic Robotics, is an evaluation designed to measure a robot's capabilities at six types of industrial tasks under different conditions. This encompasses a range of tasks, including things like tool sorting and handing, syringe packing, and cable insertion and routing. Within this, a robot can simulate "contact-rich robot-object interactions" using Nvidia's simulation technology, which is then judged on Nvidia's Isaac Lab-Arena, the open-source policy evaluation framework. 

Ken Goldberg, professor and distinguished chair in engineering at UC Berkeley, told The Deep View that the idea of agentic robotics is a fundamental shift from what many in robotics are doing, relying on a language model to write code for robots on the fly, rather than the current common paradigm of using data to improve vision-language-action models or world models. While this approach can complement those methods, it also provides its own alternative, he said. 

This method could allow robots to actually scale in production by solving the challenge of reliability, as "data-driven" approaches, which require tons of real-world data, have hit a "plateau at 80% reliability," Goldberg said. "That's good enough for writing research papers and for people to declare that as state-of-the-art, but the industry is not happy with that, and it's not enough … for an industrial application." 

Additionally, while this is scoped towards industrial use cases for now, Jim Fan, director of AI and distinguished research scientist at NVIDIA, told The Deep View that it's a "general-purpose paradigm." That means that it can eventually expand to robotic applications in retail and, eventually, home settings, serving as a step towards a major goal in the robotics industry: generalization.  

"These days, the frontier models are actually really good at generalization," said Fan. "I think agentic robotics will really help us clean up the dirty laundry that none of us want to do."

Along with potentially representing a major step towards the long held industry challenge of general-purpose robotics, Nvidia and UC Berkeley's system also counters a common industry theme that visual AI models, such as world models and vision-language-action models, are the key to solving this challenge. These types of models are often hindered in their growth by the fact that authentic, real-world data tends to be more limited than language data, something that Goldberg has pointed out in previous research on the so-called "100,000 year data gap." However, there is an additional beneficiary to agentic robotics: frontier AI labs. If agents run by large language models are put in charge of designating token-dense actions for factory robots, that could create a massive new revenue stream for the frontier labs. 

TOGETHER WITH PARLOA

Parloa puts business experts in control of agentic CX

Relying on specialized engineers to build and optimize every customer service AI agent doesn’t scale. Parloa believes CX experts, the people who are already talking to customers every single day, should be the ones in charge of what AI service agents say and do.

Parloa’s AI agent management platform lets CX teams build, optimize, and observe AI agents. Their patented Performance Flywheel™ ensures the AI improves with every interaction, turning every conversation into a loyalty-building experience.

Join Parloa on Thursday, November 19th for a hands-on agent building workshop and see their products in action.

PRODUCTS

Adobe turns rival AI into a reason to stay

As creatives brace for an AI takeover, Adobe has a different story to tell.

At its Adobe Max conference on Tuesday, the creative platform launched a suite of new AI tools across its flagship Creative Cloud tools, including Photoshop, Illustrator, Premiere, and After Effects, to automate tedious parts of the process. Most of the new features focus on unlocking a new level of precision or detail that would be time-consuming to do manually, emphasizing useful AI assistance over AI for AI's sake. 

“We're powering a new era of creativity where creators and creative professionals at every experience level have the tools, models and agents they need to bring their biggest ideas to life and stand out with work that reflects their unique taste, style and vision, while staying in control of every outcome,” said Anil Chakravarthy, Adobe's president and incoming CEO, in the release. 

There are so many features that it's difficult to list them all. Here's a quick overview of some of standout upgrades: 

• Adobe Creative Agent: This powers the Firefly AI assistant (beta) and is meant to act as a creative partner that can do tasks across apps with just a conversational text prompt. 

• Always-on agents (preview): Can do tasks in the background, like preparing social content, according to Adobe. 

• Firefly Image: Brings a new set of editing tools such as Edit Object, Relight, and Retouch. 

• Firefly Builder (private beta): Lets users create websites, presentations, or apps using natural language 

• Open Eyes: Available in public beta, replaces closed eyes with natural-looking results.

Ironically, the most impactful announcement has little to do with Adobe at all: local MCP integrations, launched in preview. This lets creatives use the third-party AI model of their choice to make local changes to their Photoshop, Illustrator, Premiere, and After Effects project files. The project's layers, vectors, bins and sequences stay editable. This is a major win for users because it reduces the need to switch between AI chatbots, especially when you have built a memory with one tool. For instance, a marketer who has already given ChatGPT all its brand assets, tone, and style won't have to re-explain them to implement those elements in an Adobe project.

There's a common misconception that AI use in creative spaces will naturally replace the artist. While some companies have tried that in the past, like the failed Coca-Cola AI holiday ad, I doubt it will work on a large scale because it always meets user pushback. What ultimately connects art with people is the story behind it, and artificially generated stories won't cut it because something feels inherently unnatural, unfamiliar, and lacking. As the title of the piece I wrote on this exact topic suggests, "AI should replace the scaffold, not the artist." It's good to see many of these Adobe tools fall into that category. 

LINKS

• NY Gov. Hochul launches first-in-the-nation state AI testing program

• AI data firm Mercor raises $750 million Series D, $20 billion valuation

• Goldman Sachs expects Anthropic revenue to hit $600 billion by 2030

• OpenAI unveils "Control Room" to track, pause risky model research 

• Anthropic discloses $10 billion commitment to Google, Microsoft

• Oura acquires AI health startup Counsel for $625 million

• Robotics firm Path raises $300 million Series E, $2.45 billion valuation

• Gemini 4 Carbon: Google's latest model is now available to developers, enterprises, scientists, and consumers.

• MiniMax H3-Image: The latest image model from Minimax, capable of 4K image generation in 10 seconds with up to 16 reference images.

• Businesses in ChatGPT: Businesses can claim, manage and get insights related to their companies in OpenAI's flagship chatbot. 

• Fish Audio Live 3: The latest model from Fish Audio, a "full-duplex" voice model that responds naturally.

• Magic Patterns: Applied AI Engineer

• Fab2: Software Engineer, AI Platform

• Poka Labs: Fullstack/AI Engineer

• Serval: Software Engineer, Agent Systems

GAMES

A QUICK POLL BEFORE YOU GO