Today @chidiwilliams__ and I are launching Sentinel. AI-driven quality assurance for CX teams in financial services.
TLDR: Weโre building https://t.co/GSo0MUt7xX to help financial services companies automate their compliance and QA with 100% coverage. We review your calls, emails, and customer support conversations for compliance violations, track performance, and create personalized AI coaching for your customer service reps.
Want to get early access, send me a DM or email [email protected] to get your team onboard.
Okay Let's just open source our YC application.
No more bringing pencils to a sword fight. We're automating back-office processes to enable fintechs and financial firms to expand compliantly. CC @t_blom@daltonc
Google presents Patchscopes
A Unifying Framework for Inspecting Hidden Representations of Language Models
paper page: https://t.co/12ucvQGmn9
Inspecting the information encoded in hidden representations of large language models (LLMs) can explain models' behavior and verify their alignment with human values. Given the capabilities of LLMs in generating human-understandable text, we propose leveraging the model itself to explain its internal representations in natural language. We introduce a framework called Patchscopes and show how it can be used to answer a wide range of research questions about an LLM's computation. We show that prior interpretability methods based on projecting representations into the vocabulary space and intervening on the LLM computation, can be viewed as special instances of this framework. Moreover, several of their shortcomings such as failure in inspecting early layers or lack of expressivity can be mitigated by a Patchscope. Beyond unifying prior inspection techniques, Patchscopes also opens up new possibilities such as using a more capable model to explain the representations of a smaller model, and unlocks new applications such as self-correction in multi-hop reasoning.
Outside of the mathematical setting, large language models can be prone to making logical mistakes. Today we present an evaluation benchmark for mistake identification across settings and examine how LLMs might learn to correct their own logical errors. โhttps://t.co/U6U5D7Libb
The most anticipated creative conference is here! ๐คฉ๐๐
Algorithm 2024 is here and it's going to be as thirlling as ever! ๐
This is where brilliance meets innovation, creatives from diverse fields will get the opportunity to collaborate, influence and occupy their space.
Brace yourself for the impact it's about to have on you as a creative.๐ฅ
Mark your calendars and get ready to be part of Algorithm 2024.
Do not miss out on the creative event of the year!๐๐พ
Secure your spot now by visiting the website in our bio for tickets.
See you there!
#cciikeja #ccilagos #algorithm
Iโll be hosting an AMA with my friend @MoVonLagos next Saturday by 6 pm WAT (via @sysdsgn).
Moses is a Staff Engineer at Google who has been promoted 3 times in 4 years โ an incredible feat, given the commonly accepted rate.
https://t.co/GnKRKhYYdU