Class-Incremental Learning (CIL) aims to continually learn new categories without forgetting previously acquired knowledge. Vision-language models such as CLIP offer strong transferable representations via multi-modal supervision, making them promising for CIL. However, applying CLIP to CIL poses two major challenges: (1) adapting to downstream tasks often requires additional learnable modules, increasing model complexity and susceptibility to forgetting; and (2) while multi-modal representations offer complementary strengths, existing methods have yet to fully realize their potential in effectively integrating visual and textual modalities. To address these issues, we propose BOFA (Bridge-layer Orthogonal Fusion for Adaptation), a novel framework for CIL. BOFA confines all model adaptation exclusively to CLIP's existing cross-modal bridge-layer, thereby adding no extra parameters or inference cost. To prevent forgetting within this layer, it leverages Orthogonal Low-Rank Fusion, a mechanism that constrains parameter updates to a low-rank ``safe subspace" mathematically constructed to be orthogonal to past task features. This ensures stable knowledge accumulation without data replay. Furthermore, BOFA employs a cross-modal hybrid prototype that synergizes stable textual prototypes with visual counterparts derived from our stably adapted bridge-layer, enhancing classification performance. Extensive experiments on standard benchmarks show that BOFA achieves superior accuracy and efficiency compared to existing methods.

Artificial intelligence is about to have its "iPhone moment" and could revolutionize everything, according to Bank of America. In a Tuesday note to clients, BofA strategists listed four reasons why AI is about to change the landscape: democratization of data, unprecedented mass adoption, "warp-speed" technological development, and abundant commercial uses. "We are at a defining moment - like the internet in the '90s - where Artificial Intelligence (AI) is moving towards mass adoption, with large language models like ChatGPT finally enabling us to fully capitalize on the data revolution," they said. Up until recently, AI could read and write but couldn't understand content, BofA said. Tools like ChatGPT have changed that, however, and its ability to understand natural language has opened the door to huge upside.

Is it possible that a mobile app used by seven million people -- and which is adding more than half a million new users per month and has already handled more that 50 million client interactions -- would not be considered a success? Even Christian Kitchell, AI Solutions and Erica Executive at Bank of America declares, "We're only in the first mile of a marathon." Forrester Principal Analyst Peter Wannemacher says Erica's number of interactions is a positive, but doesn't indicate success. He does add, however, that "Erica has been more successful than many industry insiders -- probably even Bank of America itself -- thought it would be." Bank of America's virtual financial assistant (the name is derived from the last part of "America") launched in June 2018.

Bank of America spends $3 billion developing and buying technology every year, and about three times that on keeping its existing IT infrastructure going, says David Reilly, global banking and markets technology chief information officer. As you might expect, some of that goes to artificial intelligence technology. The bank does not disclose how much. Speaking on Thursday at the bank's NYC Technology Summit, Reilly and other executives shared some of their experiences with AI and some of their concerns about it. Bank of America's chatbot, erica, which is currently available in 10 states, uses two forms of AI: natural language processing to understand speech, text and intent, as well as machine learning to glean insights from customer data that can be turned into advice and recommendations.

Recently, the CEO of Singapore's largest bank came up with the statement below; it says that in the next few decades, banks needs to put in some serious efforts for transformation or that they may die.