TL;DR:
- Toronto-based Bagel Network closes a $4.18 million CAD pre-seed funding round led by CoinFund.
- The funding round includes participation from Protocol Labs, Borderless Capital, Maven11 Capital, Graph Paper Capital, and Breed VC.
- Bagel Network aims to create a marketplace for collaboration among machine learning engineers, researchers, and AI agents for dataset building and sharing.
- Highlights the challenge of fragmented data ownership in ML and the need for unified, privacy-preserving data platforms.
- Utilizes zero-knowledge cryptography for data integrity and privacy.
- Already onboarding undisclosed data partners.
- Aims to democratize access to high-quality machine learning data for both humans and AI.
- Funding will support team growth and further development of the data ecosystem.
Main AI News:
In a significant stride towards revolutionizing the machine learning landscape, Toronto-based artificial intelligence (AI) and Web3 startup Bagel Network has successfully concluded a pre-seed funding round, amassing an impressive $4.18 million CAD ($3.1 million USD). Spearheaded by CoinFund, this funding round witnessed enthusiastic participation from notable players in the industry, including Protocol Labs, Borderless Capital, Maven11 Capital, Graph Paper Capital, and Breed VC.
Bagel Network, founded in 2023 by CEO Bidhan Roy, is pioneering the development of a novel marketplace where the collaborative efforts of machine learning engineers, researchers, and artificial intelligence (AI) agents converge to construct, exchange, and license datasets. In the realm of machine learning (ML), the pivotal task of training computers and enabling them to make informed decisions hinges on the availability of vast datasets. For instance, ChatGPT, a prominent AI model, was trained on an astounding 570 gigabytes of text data, equivalent to a staggering 300 billion words. Nevertheless, Bagel Network points out a glaring issue – a significant portion of the data used for ML model training is exclusively controlled by large corporations.
Bidhan Roy articulated this concern in a recent blog post, stating, “Despite the valiant efforts by big tech firms to aggregate training data, our datasets remain fragmented across sectors, access models, and private big tech silos. We desperately need unified platforms enabling the seamless flow of data between individuals, companies, and AI agents in a privacy-preserving manner.”
Bagel Network’s distinctive approach incorporates decentralization, leveraging zero-knowledge cryptography to uphold the integrity and privacy of data. As reported by The Block, the startup has already initiated the onboarding of undisclosed data partners into its network, signifying a promising trajectory for the platform.
Roy envisions a future where top-tier, planet-scale machine learning data becomes effortlessly accessible to both human users and artificial intelligence entities. He further remarked, “By transforming the data economy with incentivized, privacy-preserving mechanisms, we will catalyze significant advancements in AI.”
The infusion of capital garnered from this funding round will be channeled towards Bagel Network’s internal expansion, including team augmentation, which currently stands at five members according to The Block. Additionally, a significant portion of the funds will be dedicated to the further development of the data ecosystem, solidifying Bagel Network’s commitment to reshaping the landscape of machine learning.
With its innovative vision and substantial financial backing, Bagel Network is poised to play a pivotal role in redefining the way machine learning data is accessed, shared, and utilized in the future of artificial intelligence.
Conclusion:
Bagel Network’s successful funding round signifies growing investor confidence in the potential of democratizing access to high-quality machine learning data. This development is indicative of a shifting landscape where data ownership and accessibility become more inclusive, promising significant advancements in the AI market. As Bagel Network continues to develop its platform, it could foster a more competitive and collaborative environment for AI innovation, ultimately reshaping the machine learning industry.
