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February 26.2025
3 Minutes Read

BNY Mellon Partners with OpenAI to Transform Its Eliza AI Platform

BNY Mellon building entrance with man walking in daylight.

BNY Mellon Partners with OpenAI to Transform Its Eliza AI Platform

The Bank of New York Mellon (NYSE: BK), one of America's oldest financial institutions, has taken a significant step into the future of artificial intelligence by sealing a multi-year partnership with OpenAI. This collaboration is set to bolster its proprietary AI platform, Eliza, leveraging OpenAI's advanced technologies to reshape how financial services operate.

A New Era for Eliza

With this agreement, BNY Mellon aims to further enhance Eliza, which serves as the foundational AI system for the bank. The partnership grants access to OpenAI’s state-of-the-art API and ChatGPT Enterprise platforms, invigorating Eliza with capabilities such as improved reasoning models and fine-tuning options. This expansion signals a robust commitment to integrating AI across all levels of service and operations.

Harnessing AI for Financial Services

AI is increasingly becoming central to the financial services sector, promoting efficiency and innovation. BNY Mellon currently operates about 40 AI-enabled solutions that are already enhancing predictive analytics, automation, and anomaly detection within the bank. Integrating OpenAI's expertise may not only refine these existing tools but also set the stage for new capabilities that can revolutionize client servicing and operational workflows.

What's in Store for the Future? Insights and Predictions

Leigh-Ann Russell, BNY's Chief Information Officer, stated, "AI is reshaping the landscape of financial services and helping us to move quicker, be more efficient and resilient." This statement highlights a broader trend in the financial industry, where companies are increasingly focused on adopting AI solutions to meet fast-evolving consumer needs. Furthermore, as AI technologies continue to advance, BNY Mellon may soon offer innovative products that were previously unimaginable.

Embracing a Cultural Shift

The integration of AI is not just a technological shift but a cultural transformation within BNY Mellon. The Eliza platform encourages all employees to harness AI capabilities to streamline workflows and drive innovative thinking. More than half of the workforce engages with Eliza regularly, with a notable portion proficient enough to develop their AI agents. This democratization of AI usage within the bank may inspire employees to approach challenges creatively and collaboratively.

Challenges and Opportunities

While the potential for AI in finance is vast, challenges such as data privacy, regulatory compliance, and the need for transparency must be addressed. As BNY Mellon ventures deeper into AI integration, it will be critical to establish governance frameworks that reassure stakeholders and build trust in AI systems. Striking the right balance between harnessing technology and ensuring ethical standards will be paramount.

The Broader Impact of AI on the Financial Sector

The implications of BNY Mellon's partnership with OpenAI extend beyond the bank itself, highlighting a growing trend toward AI adoption across the industry. Other financial institutions may follow suit, racing to integrate similar technologies to remain competitive. As AI systems like Eliza become integral to banking operations, customers can expect faster, more personalized services, reshaping the way they interact with their financial institutions.

As the financial landscape increasingly favors organizations that leverage cutting-edge technology, BNY Mellon’s innovative alignment with OpenAI could set new standards within the sector.

Staying informed about such significant developments in AI can empower enthusiasts to think critically about the technology's impact on financial services and society at large. If you’re keen on following the latest in AI innovations and their implications, engage with the thriving communities of tech and finance enthusiasts.

Open AI

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04.02.2025

Examining OpenAI's Use of Copyrighted Data: Insights from Recent Studies

Update OpenAI's Copyright Controversy: What You Need to Know A recent study brings to light significant ethical concerns regarding the training practices of OpenAI's language models, particularly focusing on the GPT-4o model. The research conducted analyzed whether OpenAI utilized copyrighted material without consent, raising alarm bells in the tech community. This inquiry is especially pertinent for AI enthusiasts who are keen on understanding the legal and social implications of machine learning technologies. Key Findings from the New Study The study was able to effectively utilize DE-COP membership inference attack methods, allowing researchers to evaluate the ability of the GPT-4o model in recognizing contents gleaned from copyrighted O’Reilly Media books. In stark contrast to its predecessor, GPT-3.5 Turbo, which only displayed minimal recognition capabilities, the GPT-4o demonstrated a noteworthy AUROC score of 82% when assessing contents from paywalled O’Reilly books. This statistic indicates the model's strong ability to discern between human and machine-generated text, raising critical questions about data usage in machine training. Systemic Issues in AI Training Data While the results are specifically tied to OpenAI and O’Reilly Media, they illuminate a crucial point: the tech industry may be grappling with broader issues surrounding the use of copyrighted materials. The researchers hint at potential access violations stemming from the LibGen database, where all tested O’Reilly books were evidently available. This points towards possible systemic exploitation of copyrighted data across various platforms, prompting urgent discussions around fair educational practices in AI research. The Role of Temporal Bias in AI Recognition Another layer discussed in the study is the concept of temporal bias—the idea that the language and contextual understanding evolve over time. The researchers took measures to mitigate this bias by ensuring both models analyzed (GPT-4o and GPT-4o Mini) were trained on data from the same time period. This meticulous approach demonstrates the researchers' commitment to isolating the effects of temporal change on AI model training, further establishing the credibility of their findings. Impact on Content Quality and Diversity The implications of this study extend beyond legal boundaries into the realm of content quality. The unchecked practice of training AI models using copyrighted data could lead to a significant decline in the diversity and richness of content found on the internet. If major tech companies exploit creative works without compensation properly, they risk robbing authors and creators of their livelihoods and undermining the very fabric of creative growth in the digital age. Building a Framework for Ethical AI For AI enthusiasts and developers, this study serves as a clarion call to reassess the ethical dimensions of machine learning frameworks. OpenAI's case spotlighted a critical need for stricter guidelines and governance surrounding AI training methodologies. The fallout from unethical data usage could not only stifle innovation but could also create a culture of distrust in AI capabilities. In conclusion, as the debate over copyright and AI training practices evolves, it becomes increasingly essential for enthusiasts and developers alike to champion ethical methods of training AI models. With pressure mounting for transparency and integrity in the tech space, the collective responsibility lies in ensuring that AI models are developed in a manner that respects and protects creative rights. The rich conversation surrounding these findings can catalyze changes in policy and practice, calling for more informed discussions about the ethical dimensions of AI.

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