Bardeen, a provider of AI agents capable of automating repetitive knowledge work using a natural language interface, unveiled its Work Intelligence Platform—a new system of AI agents that learn how work actually happens, then executes and improves it without any hand-holding. True operational intelligence is capable of identifying how top performers work and scaling that knowledge across an organization. With its Work Intelligence Platform, Bardeen is bringing that level of understanding to the broader market, making go-to-market execution consistent and scalable. The new platform is underscored by Bardeen’s belief that automation should interpret before it acts, and that the next generation of AI should understand how work happens and improves it in real-time. Bardeen’s Work Intelligence Platform: Securely observes task-level behavior across all tools, including Salesforce, LinkedIn, Salesloft, and HubSpot, and reveals how individuals and teams actually work; Surfaces hidden workflows, exposes time sinks and inefficiencies, and highlights high-leverage patterns that drive performance; Automates entire workflows with AI-generated automation agents tailored to the way teams already work
DarkBench is the first benchmark designed specifically to detect and categorize LLM dark patterns, AI sycophancy, brand bias or emotional mirroring
Esben Kran, founder of AI safety research firm Apart Research, and his team approach large language models (LLMs) much like psychologists studying human behavior. Their early “black box psychology” projects analyzed models as if they were human subjects, identifying recurring traits and tendencies in their interactions with users. “We saw that there were very clear indications that models could be analyzed in this frame, and it was very valuable to do so, because you end up getting a lot of valid feedback from how they behave towards users,” said Kran. Among the most alarming: sycophancy and what the researchers now call LLM dark patterns. Kran describes the ChatGPT-4o incident as an early warning. As AI developers chase profit and user engagement, they may be incentivized to introduce or tolerate behaviors like sycophancy, brand bias or emotional mirroring—features that make chatbots more persuasive and more manipulative. To combat the threat of manipulative AIs, Kran and a collective of AI safety researchers have developed DarkBench, the first benchmark designed specifically to detect and categorize LLM dark patterns. Their research uncovered a range of manipulative and untruthful behaviors across the following six categories: Brand Bias, User Retention, Sycophancy, Anthropomorphism, Harmful Content Generation, and Sneaking. On average, the researchers found the Claude 3 family the safest for users to interact with. And interestingly—despite its recent disastrous update—GPT-4o exhibited the lowest rate of sycophancy. This underscores how model behavior can shift dramatically even between minor updates, a reminder that each deployment must be assessed individually. A crucial DarkBench contribution is its precise categorization of LLM dark patterns, enabling clear distinctions between hallucinations and strategic manipulation. Labeling everything as a hallucination lets AI developers off the hook. Now, with a framework in place, stakeholders can demand transparency and accountability when models behave in ways that benefit their creators, intentionally or not.
Databricks acquisition of Neon to offer enterprises ability to deploy AI agents at scale by rapidly spinning up databases programmatically without coupling storage and compute needs, through a serverless autoscaling approach to PostgreSQL
Databricks announced its intent to acquire Neon, a leading serverless Postgres company. Neon’s serverless PostgreSQL approach separates storage and compute, making it developer-friendly and AI-native. It also enables automated scaling as well as branching in an approach that is similar to how the Git version control system works for code. Amalgam Insights CEO and Chief Analyst Hyoun Park noted that Databricks has been a pioneer in deploying and scaling AI projects. Park explained that Neon’s serverless autoscaling approach to PostgreSQL is important for AI because it allows agents and AI projects to grow as needed without artificially coupling storage and compute needs together. He added that for Databricks, this is useful both for agentic use cases and for supporting the custom models they have built over the last couple of years after its Mosaic AI acquisition. For enterprises looking to lead the way in AI, this acquisition signals a shift in infrastructure requirements for successful AI implementation. What is particularly insightful, though, is that the ability to rapidly spin up databases is essential for agentic AI success. The deal validates that even advanced data companies need specialized serverless database capabilities to support AI agents that create and manage databases programmatically. Organizations should recognize that traditional database approaches may limit their AI initiatives, while flexible, instantly scalable serverless solutions enable the dynamic resource allocation that modern AI applications demand. For companies still planning their AI roadmap, this acquisition signals that database infrastructure decisions should prioritize serverless capabilities that can adapt quickly to unpredictable AI workloads. This would transform database strategy from a technical consideration to a competitive advantage in delivering responsive, efficient AI solutions.
Databricks acquisition of Neon to offer enterprises ability to deploy AI agents at scale by rapidly spinning up databases programmatically without coupling storage and compute needs, through a serverless autoscaling approach to PostgreSQL
Databricks announced its intent to acquire Neon, a leading serverless Postgres company. Neon’s serverless PostgreSQL approach separates storage and compute, making it developer-friendly and AI-native. It also enables automated scaling as well as branching in an approach that is similar to how the Git version control system works for code. Amalgam Insights CEO and Chief Analyst Hyoun Park noted that Databricks has been a pioneer in deploying and scaling AI projects. Park explained that Neon’s serverless autoscaling approach to PostgreSQL is important for AI because it allows agents and AI projects to grow as needed without artificially coupling storage and compute needs together. He added that for Databricks, this is useful both for agentic use cases and for supporting the custom models they have built over the last couple of years after its Mosaic AI acquisition. For enterprises looking to lead the way in AI, this acquisition signals a shift in infrastructure requirements for successful AI implementation. What is particularly insightful, though, is that the ability to rapidly spin up databases is essential for agentic AI success. The deal validates that even advanced data companies need specialized serverless database capabilities to support AI agents that create and manage databases programmatically. Organizations should recognize that traditional database approaches may limit their AI initiatives, while flexible, instantly scalable serverless solutions enable the dynamic resource allocation that modern AI applications demand. For companies still planning their AI roadmap, this acquisition signals that database infrastructure decisions should prioritize serverless capabilities that can adapt quickly to unpredictable AI workloads. This would transform database strategy from a technical consideration to a competitive advantage in delivering responsive, efficient AI solutions.
Windsurf’s new frontier-class AI models focus on specific engineering tasks as against LLMs that gear towards general-purpose coding; adopt ‘flow awareness’ that progressively transfer tasks from human to AI through a shared timeline of actions to accelerate the entire development lifecycle
To date, vibe coding platforms have largely relied on existing large language models (LLMs) to help write code. Windsurf is taking on the challenge with a series of new frontier AI models it calls SWE-1 (software engineer 1) as part of the company’s Wave 9 update. SWE-1 is a family of frontier-class AI models specifically designed to accelerate the entire software engineering process. Available immediately to Windsurf users, SWE-1 marks the company’s entry into frontier model development with performance competitive to established foundation models, but with a focus on software engineering workflows. Anshul Ramachandran, head of product and strategy at Windsurf, said, “The core innovation behind SWE-1 is Windsurf’s recognition that coding represents only a fraction of what software engineers actually do.” Rather than creating a one-size-fits-all solution, Windsurf has developed three specialized models: SWE-1; SWE-1-lite and SWE-1-mini. T he goal is to position SWE-1 as the first step toward purpose-built models that will eventually surpass general-purpose ones for specific engineering tasks — and potentially at a lower cost. What makes Windsurf’s approach technically distinctive is its implementation of the flow awareness concept. Flow awareness is centered on creating a shared timeline of actions between humans and AI in software development. The core idea is to progressively transfer tasks from human to AI by understanding where AI can most effectively assist. This approach creates a continuous improvement loop for the models. For enterprises building or maintaining software, SWE-1 represents an important evolution in AI-assisted development. Rather than treating AI coding assistants as simply autocomplete tools, this approach promises to accelerate the entire development lifecycle. The potential impact extends beyond just writing code more quickly. The recognition that application development is more involved will help mature the vibe coding paradigm to be more applicable for stable enterprise software development. If and when OpenAI completes the acquisition of Windsurf, the new models could become even more important as they intersect with the larger model research and development resources that will become available.
Microsoft wants in-house AI ‘agents’ to work together with external agents in a collaboration and remember such interactions
Microsoft envisions a future where any company’s artificial intelligence agents can work together with agents from other firms and have better memories of their interactions, its chief technologist said on Sunday ahead of the company’s annual software developer conference. Microsoft is holding its Build conference in Seattle on May 19, where analysts expect the company to unveil its latest tools for developers building AI systems. Speaking at Microsoft’s headquarters in Redmond, Washington, ahead of the conference, Chief Technology Officer Kevin Scott told reporters and analysts the company is focused on helping spur the adoption of standards across the technology industry that will let agents from different makers collaborate. Agents are AI systems that can accomplish specific tasks, such as fixing a software bug, on their own.
Microsoft wants in-house AI ‘agents’ to work together with external agents in a collaboration and remember such interactions
Microsoft envisions a future where any company’s artificial intelligence agents can work together with agents from other firms and have better memories of their interactions, its chief technologist said on Sunday ahead of the company’s annual software developer conference. Microsoft is holding its Build conference in Seattle on May 19, where analysts expect the company to unveil its latest tools for developers building AI systems. Speaking at Microsoft’s headquarters in Redmond, Washington, ahead of the conference, Chief Technology Officer Kevin Scott told reporters and analysts the company is focused on helping spur the adoption of standards across the technology industry that will let agents from different makers collaborate. Agents are AI systems that can accomplish specific tasks, such as fixing a software bug, on their own.
Capital One closes Discover acquisition with stipulations to address Discover’s outstanding enforcement actions; will reportedly pay $425 million to settle a lawsuit accusing it of cheating savings account depositors
Armed with Discover’s payments network, which competes with those of Visa Inc. and Mastercard Inc., Capital One is poised to capture an even greater share of spending on credit and debit cards that Americans so heavily rely upon. “We are well-positioned to continue our quest to change banking for good for millions of customers,” Capital One Chief Executive Officer Richard Fairbank said. The acquisition wasn’t assured, given the last presidential administration’s skepticism of mergers — and especially those involving finance firms. Bank dealmaking activity was stunted during Joe Biden’s presidency, and some Congressional Democrats opposed the Capital One takeover of Discover, saying it may harm consumers and put the stability of the US financial system at risk. With Donald Trump now in the Oval Office, the Federal Reserve and the Office of the Comptroller of the Currency approved the deal last month after the US Department of Justice decided not to challenge it. But the approval came with stipulations: the OCC mandated that Capital One outline the corrective actions it planned to take to address Discover’s outstanding enforcement actions. In 2023, the firm disclosed that, starting in 2007, it had been charging merchants more than it should have to accept payments on certain credit cards. In connection with the acquisition, Capital One is expanding its board of directors to 15 members from 12. Capital One and Discover customer accounts and banking relationships remain unchanged for now, and information in advance of any forthcoming changes will be provided, according to the statement.
Citi Community Capital retained its spot at the top in Affordable Housing Finance’s Top 25 affordable housing lenders of 2024; KeyBank was second and BoA ranked third
Despite difficulties many lenders lent more in 2024 to affordable housing properties. Affordable Housing Finance’s Top 25 affordable housing lenders provided $60.1 billion in permanent and construction loans in 2024 to developments that serve households up to 80% of the area median income (AMI). That’s an increase from the more than $55.7 billion in loans provided by 2023’s top lender list. Citi Community Capital retained its spot at the top of the list. It lent just over $7 billion to affordable housing properties last year, just slightly above the nearly $6.5 billion in 2023. Because of today’s uncertainties, Citi forecasts it will lend just $6 billion to affordable housing properties this year. However, if federal funding levels stabilize, Citi could easily beat that conservative forecast and build on the amount it lent in 2024, Johnson notes. Citi is also confident that the forecast will not sink lower than $6 billion for 2025. A portion of those loans are conversions of construction loans to permanent financing for projects that have already fixed their sources and uses of funds. Bank of America Community Development Banking provided a construction loan in mid-2024 and invested in tax credits for the $83.5 million project. Grants, soft financing, and a partially deferred developer fee provided much of the rest of the financing, including a Rhode Island Renewable Energy Grant and funds from the Providence Housing Trust Fund, the Rhode Island Housing Rebounds Fund, and the Federal Home Loan Bank of Boston. J.P. Morgan created its Workforce Housing Solutions group to finance projects like this. It closed its first construction loan in December 2023 to finance a new community built with modular housing, now scheduled to open this summer in Los Angeles. In June 2024, Roers Cos., a national multifamily real estate investment firm, closed the financing to develop 200 new apartments at Allers Landing in Austin, Texas. J.P. Morgan provided a $29.2 million construction loan to help build Allers Landing. The $55.9 million project will include 110 workforce housing apartments reserved for households earning up to 80% of the area median income.
U.S. Bank launches extension of The Power of Us campaign to “demonstrate the power of the interconnected bank” and highlighting goal savings digital budgeting, business growth and cash back features
Last May, U.S. Bank launched its brand campaign, The Power of Us, which highlighted how it supports clients at every stage of their journey to help them reach their goals. Now, U.S. Bank is building on that momentum by launching an extension of last year’s campaign that is focused on how great things can be achieved by working alongside its clients. The new campaign focuses on sharing stories that reflect the diversity of its businesses, reinforce its distinct style of partnership and demonstrate the interconnected nature of its products and services. “This new campaign builds on the strong foundation we laid last year,” said Michael Lacorazza, chief marketing officer for U.S. Bank. “It brings to life the collaborative spirit that defines our brand. By showcasing the range of our businesses and the strength of our partnerships, we’re telling a powerful story about what we can achieve together.” Like last year’s brand campaign, U.S. Bank is putting a spotlight on the brand’s most iconic assets—name, shield, color palette — and continuing to infuse multicultural insights throughout the brand campaign assets. Actor Jake Gyllenhaal also is back as the voice of the campaign spots, adding a distinct tone with subtle gravitas.
- The Power of Jess: Featuring Jess Sims, an entrepreneur, Peloton Instructor, educator, sideline reporter and game changer, this spot shows how U.S. Bank Smartly® Checking and Savings helps her achieve her goals faster.
- The Power of Mia: This highlights an entrepreneur who uses U.S. Bank Business Essentials® to manage her growing business with ease.
Under Control: Mari surprises her dad with a car and explains how Bank Smartly® digital budgeting tools and cash back from her U.S. Bank Smartly™ Checking and Savings helped make it possible. This spot grew from an insight about the daughter’s role as the CFO for her family and was produced as a bilingual commercial that will run in both English- and Spanish-language media.