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A Vast New Data Set Could Supercharge the AI Hunt for Crypto Money Laundering
Nex AI News
Nex AI
May 02, 2024
A Vast New Data Set Could Supercharge the AI Hunt for Crypto Money Laundering
Thursday - May 2 - 2024
AI's prowess in analyzing extensive data is revolutionizing Bitcoin blockchain scrutiny.
Researchers from Elliptic, MIT, and IBM have devised a novel AI model for detecting suspicious bitcoin transactions by identifying transaction patterns linked to money laundering.
Airbnb’s summer release has introduced updates primarily for group bookings, featuring shared wishlists and detailed trip invitations.
Additionally, a new category called “Icons” offers unique experiences with notable figures in entertainment and sports.
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Today’s newsletter :
A Vast New Data Set Could Supercharge the AI Hunt for Crypto Money Laundering
Airbnb releases group booking features as it taps into AI for customer service
How to Use ChatGPT’s Memory Feature
Natural language boosts LLM performance in coding, planning and robotics
Science has an AI problem: Research group says they can fix it
How to build and protect skills in our modern workplace, a world filled with AI and robots
AMD is the latest company to show that AI is an expensive proposition
6 Latest AI Models from Meta, OpenAI, Apple and More
AI Drug Discovery Startup Emerges From Stealth, Raises $1B
AI's prowess in analyzing extensive data is revolutionizing Bitcoin blockchain scrutiny.
Researchers from Elliptic, MIT, and IBM have devised a novel AI model for detecting suspicious bitcoin transactions by identifying transaction patterns linked to money laundering.
This approach, backed by a 200-million transaction dataset, marks a significant shift in blockchain analytics.
The potential of this data, published on Kaggle, extends beyond its immediate application, promising to enhance anti-money-laundering efforts and foster broader AI research into financial crimes.
Airbnb’s summer release has introduced updates primarily for group bookings, featuring shared wishlists and detailed trip invitations.
Additionally, a new category called “Icons” offers unique experiences with notable figures in entertainment and sports.
Significant for group travel, users can invite others to join a wishlist via contacts or a link, collaboratively add properties, and vote on them.
Once a property is booked, a detailed invitation is sent to confirm travel arrangements.
Hosts now benefit from an AI-powered message tab for efficient communication and AI-suggested replies, enhancing the overall hosting experience.
Furthermore, Airbnb is improving host tools with a new earnings dashboard and testing AI for customer support, aimed at providing succinct summaries and efficient query resolution.
This evolution in service is part of Airbnb's broader strategy to enhance user experience through technology.
OpenAI has introduced a "Memory" feature for ChatGPT Plus subscribers, enhancing the AI's ability to hold and utilize information across sessions.
Initially tested with a small user group, this feature is now available to Plus subscribers, although not yet in Europe or Korea.
It allows ChatGPT to store details from conversations, like preferences and personal data, which it references in future interactions.
Users can manage what the AI remembers through settings, adding or removing data as desired.
This move marks a significant step toward more personalized and fluid AI conversations, reminiscent of AI interactions depicted in sci-fi narratives.
However, it also raises privacy concerns, prompting options to opt out of data usage for model training.
Researchers at MIT's CSAIL are exploring advanced uses of large language models (LLMs) to bridge the gap between AI and human reasoning capabilities.
They have developed three frameworks—LILO, Ada, and LGA—each aimed at enhancing AI's ability to abstract complex concepts from natural language, thereby improving its performance across diverse domains such as code synthesis, AI planning, and robotics.
LILO refactors code into more manageable libraries, Ada aids AI in developing sequential decision-making skills, and LGA enables robots to better interpret their environments.
These systems, described in papers to be presented at the International Conference on Learning Representations, utilize a neurosymbolic approach that combines neural networks with logical components, marking a significant step toward more human-like AI by using everyday language as a rich source of context.
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Science has an AI problem: Research group says they can fix it
A team of interdisciplinary researchers, led by Princeton University's Arvind Narayanan and Sayash Kapoor, has published guidelines aimed at addressing the deep flaws in how machine learning is used in scientific research.
As machine learning applications become widespread across numerous disciplines, the potential for errors increases significantly, risking what Narayanan refers to as a reproducibility crisis.
How to build and protect skills in our modern workplace, a world filled with AI and robots
Matt Beane, assistant professor at UC Santa Barbara, addresses the impact of intelligent machines on workplace training in his book "The Skill Code."
He argues that while technologies like surgical robots enhance productivity, they disrupt the essential master-novice relationship critical for skill development.
AMD is the latest company to show that AI is an expensive proposition
AMD's recent earnings highlighted significant investment in its AI technology, particularly in its MI300 accelerator, amid increasing costs and high market expectations.
Although these investments are driving higher operational expenses, lowering the gross-margin profile for AMD's data-center GPUs compared to its overall data-center operations, analysts like Cantor Fitzgerald's C.J. Muse and Baird's Tristan Gerra recognize the potential long-term benefits.
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