Toward a future that preserves benefits of neurotechnology for all
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
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Toward provably private learning from federated data
Mobile Systems
Introducing SynthID Bio
Proof of concept for watermarking AI-generated proteins while preserving biological function.
Introducing Quine: An AI research system designed for the complexity of biology
Biology doesn't operate in silos, and neither should the AI representation of it. Quine is an early-stage research effort to create a multimodal world model of biology. By connecting insights across biological scales and modalities, Quine helps scientists computationally search a space far larger than intuition allows and prioritize hypotheses before they reach the lab. Experimental results provide important feedback, helping researchers sharpen future research directions. The post Introducing Q…
The effects of an “algorithmic monoculture” depend on the details
In a study focusing on hiring decisions, MIT researchers found the use of a single algorithm by many firms could benefit job seekers in certain situations.
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Scrum in a Multiproject Environment: An Ethnographically-Inspired Case Study on the Adoption Challenges
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoptio...
Making the leap to a software platform strategy: Issues and challenges
A comprehensive taxonomy of the challenges faced when a medium-scale organization decided to adopt software platforms is provided, namely: business challenges, organizational challenges, technical challenges, and people challenges.
A framework for systematic analysis of open access journals and its application in software engineering and information systems
It is shown that high article processing charges are not sufficiently justified by the publishers, which often lack transparency and may prevent authors from adopting OA.
PepPCBench is a Comprehensive Benchmarking Framework for Protein-Peptide Complex Structure Prediction
PepPCBench enables a robust evaluation of PFNN-based methods and supports their continued development for peptide-protein structure prediction, and highlights the influence of peptide length, conformational flexibility, and training set similarity on prediction accuracy.