Block Launches Open-Source AI Agent Goose As Jack Dorsey Praises DeepSeek's Development Approach
With the success of DeepSeek, AI development could see a paradigm shift toward a more open-source approach—a trend that Block said is already in motion. “We want open by default to be a North Star”
On Tuesday, the software company Block announced the launch of Goose, an open-source AI agent that allows developers to customize the tool for different purposes and using different large language models.
The move comes just a week after the Chinese startup DeepSeek unveiled its R1 artificial intelligence model, a rival to U.S. leaders like OpenAI and Anthropic that boasted far lower development costs. While the launch continues to reverberate through the tech world, spurring the chipmaker Nvidia to lose $600 billion in market cap, one clear winner has emerged: open-source software like Goose. Where companies like OpenAI favor a closed model, DeepSeek makes its underlying code public, meaning other developers can use and modify it.
The surprise breakout of DeepSeek has brought the debate over open versus closed-source development into the forefront, with software engineers and tech leaders long arguing over the best approach to advance innovation. Jack Dorsey, the head of Block and former Twitter CEO, took the opportunity to make his own preferences clear. “Open source everything,” he posted on X on Monday.
Dorsey has long been a champion of open-source development, with Block working on landmark projects like the cross-computer gRPC communication protocol, and his company is doubling down on the approach. Last Tuesday, Block announced the opening of its Open Source Program Office, which will house five engineers who help work across the company’s suite of products, including Cash App, Square, and Tidal.
Today’s launch of Goose allows users to connect with large language models like OpenAI’s o1 or DeepSeek’s R1 to perform real-world tasks, from checking code for bugs to sending emails. In an interview with Fortune, Block’s open-source lead Manik Surtani said the approach is the “best way to build software.”
“It’s even more important for a financial services company to be building on open principles and open standards,” he said. “That is what everyone really wants. They want transparency.”
More on Block’s AI programming agent and open posture
How to Create Business Value With AI
In this episode of Top of Mind, Gartner Global Chief of Research Chris Howard is joined by Rita Sallam, Distinguished VP Analyst, to explore how organizations can create measurable value with AI in 2025.
Learn how to align investments with business priorities, manage productivity challenges and balance risk with ambition in today’s AI environment.
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Cerebras AI And Mayo Clinic Debut A World-Class Genomic Foundation Model
One of the most compelling use cases of AI is in healthcare, and over the past couple of years, the medical community has learned that there are a lot of different applications, not just one.
People often start by talking about improvements and diagnosis and treatment, and that is central to the clinical process. But AI can benefit patients in many other ways, too. There’s everything from billing and scheduling, to the critical use of real-time vital signs to look for risk.
However, focusing on those broader-spectrum goals, we have news from AI company Cerebras and the Mayo Clinic, announcing a joint project for AI tools used in patient care. The technology was announced at the JP Morgan Healthcare Conference in San Francisco.
In this project, the stakeholders aim to use a human reference genome to combine with patient data in order to try to identify genetic differences against benchmarks, and apply that to treating patients. The model was trained using data on 500 Mayo Clinic patients, and the genomic data.
A Quick Glossary
The Cerebras press release points out that system uses Mayo Clinic’s “patient exome data.” What is exome data? Here’s what ChatGPT says:
“Exome data refers to information obtained by sequencing all of the protein-coding regions of the genome—known collectively as the ‘exome.’ These protein-coding regions (called ‘exons’) represent only about 1–2% of the entire human genome but contain the vast majority of known disease-related genetic variations. By focusing on the exome, researchers and clinicians can more efficiently identify disease-causing variants without having to sequence and analyze the entire genome.”
And what is the human reference genome? Scientists describe it as a composite “idealized” version of a human genome, a sort of boilerplate template to serve as a control case for genomic variations.
More on Cerebras’ world-class genomic foundation model on Forbes
How Human Should an AI Chatbot Be?
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DeepSeek Now In Perplexity’s AI Search— U.S. AI Dominance Challenged
China’s open-source DeepSeek begins to integrate with major international AI players, as these companies start leveraging DeepSeek’s capabilities to enhance their own. U.S.-based Perplexity AI leads the charge, incorporating DeepSeek's innovative R1 reasoning model into its platform to revolutionize AI-powered search. This strategic integration strengthens Perplexity’s ability to perform deep web searches, providing users with more comprehensive and accurate results while upholding strict data security standards.
DeepSeek’s Smart Use of Existing Tech
The DeepSeek R1 model, developed by the Chinese AI startup DeepSeek, is designed to excel in complex reasoning tasks. It utilizes a Mixture-of-Experts (MoE) architecture, which activates only a fraction of its parameters at a time, significantly reducing computational costs and improving efficiency. This approach allows R1 to perform on par with advanced models like OpenAI's ChatGPT-4o and ChatGPT-o1, but at a fraction of the cost for API connections.
R1's integration into Perplexity AI enhances the platform's deep web research capabilities, enabling users to explore vast amounts of data with unprecedented depth and accuracy1. The model's sophisticated reasoning abilities, combined with Perplexity's existing search algorithms, create a synergistic effect that improves the quality and relevance of search results.
Industry Context and Recent Developments
The AI industry has been rapidly evolving, with a focus on developing more efficient and cost-effective models. DeepSeek's approach of using trial and error for self-improvement mimics human learning processes, setting it apart from traditional AI training methods. This innovative technique has allowed DeepSeek to develop its models quickly and efficiently, disrupting the market with free access. Perplexity AI's decision to integrate R1 comes at a time when AI-powered search is gaining traction. The company was among the first to combine Google-style search engines with ChatGPT-style conversational abilities, beating both Google and OpenAI to market with this hybrid approach. The addition of R1 further solidifies Perplexity's position as a leader in AI-powered search technology.
More on Perplexity’s DeepSeek integration on Forbes
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Atomicwork Raises $25 Million To Capitalize On Artificial Intelligence
San Francisco-based start-up Atomicwork will today announce it has clinched $25 million of Series A financing in a round led by Khosla Ventures and Z47. The funding announcement comes less than six months after the company’s last round, I wrote about last year, and takes the total amount of money raised by the company since its launch in 2022 to almost $40 million.
Atomicwork started out with a software solution aimed at improving the employee experience by linking up all the different tools that individuals use to do their work. The idea was that by ensuring much more seamless connections between software such as Slack, Microsoft’s Office range and email tools, for example, employees will waste less time having to swap from one to the other. That should drive increased productivity across the organisation.
More recently, Atomicwork has increased the extent to which artificial intelligence is incorporated into its solutions, using AI agents to manage the interactions between different tools and to take on more manual work. The goal is to simplify enterprise workflows and to free up employees’ time for more value-additive tasks.
“The pace has really picked up over the past six months,” says Vijay Rayapati, co-founder and CEO of the company. “We’re helping teams to do their jobs better and to work smarter, but also to offload the tasks that take up so much of their time; AI agents have enabled us to really accelerate the options we offer.”
Atomicwork’s investment in its technology has delivered immediate returns, with the company’s growth also jumping ahead since its last fundraising. The company’s workforce has doubled in size to around 70 and Rayapati is now targeting annual revenues in excess of $10 million. “The opportunity is incredible,” he says. “We really believe we’re going to build a next-generation company.”
More on Atomicwork’s funding and growth plans on TechCrunch
Wolf: The Power Of Open-Sourced AI
Thomas Wolf, chief science officer at Hugging Face, says DeepSeek's open-source model allows sharing of information, helping to lift all AI progress. He joins Caroline Hyde and Mike Shepard on "Bloomberg Technology" to discuss.
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