research
research on Beyond Market Intelligence: a running collection of 11 stories we have gathered and hand-picked because they are worth your time. Every post here touches on research in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around research, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
AAAI 27 AI Alignment track [D]
Navigating the AI Alignment track at AAAI 27 can feel opaque. Submission details for track [D] appear exclusively on OpenReview, accessible here: [link]. This track, alongside the Artificial Intelligence for Social Impact, Conference, and Innovative Applications of AI tracks, represents a crucial intersection of research and real-world impact. Understanding the submission process is key to contributing to this vital area. For deeper insight into the evolving landscape of AI progress, explore our analysis of the recent DeepMind/Kaggle challenge, "Measuring Progress Toward AGI – Cognitive Abilities."
NeurIPS reviews coming in soon! [D]
NeurIPS reviews are anticipated to appear around July 22nd at 5:30 PM AoE, based on observations across social platforms. For those who submitted to NeurIPS 2026 – whether to workshops or the main/other tracks – we'd welcome your perspectives on the upcoming reviews. This period marks a critical juncture for researchers. Explore insights into model performance; for example, our recent article on "Schema," a harness achieving 99% on ARC-3, offers a relevant case study in pushing boundaries. Share your thoughts and prepare for the assessments!
![Prism accidentally leaked [D]](https://preview.redd.it/csr59ogtwtdh1.png?width=140&height=27&auto=webp&s=d8b3c46b64b19d75c4b2b1726b0b3cbea225f38d)
Prism accidentally leaked [D]
A recent, swiftly addressed incident at Prism highlights a critical concern in the AI research space. A data leak inadvertently resulted in the compilation and distribution of another researcher's paper, a situation quickly acknowledged and rectified by Prism's team, who took their website offline within ten minutes of initial reports. While their responsiveness is commendable, the incident raises valid questions about data security and the potential for unintentional intellectual property breaches.
AI/ML Research - What Does it Really Take? [D]
Embarking on a career in AI/ML research demands dedication and a clear vision. This exploration delves into the realities of pursuing that path, particularly at the intersection of audio and artificial intelligence. Driven by a passion for combining audio engineering expertise with advanced AI techniques, the author details their journey—from coding bootcamps to master's studies—and the challenges encountered. See related coverage on recent advancements, such as the "New Fable5/Opus4.8 harness called "Schema" claims 99% on ARC-3," for further insights into current trends.
short-paper at ACL/EMNLP/EACL [R]
Navigating the short-paper submission process for ACL/EMNLP/EACL can be challenging. Acceptance rates for these concise submissions often lag behind those of full-length papers, and understanding the landscape is key. We're seeking insights from anyone who has successfully had a short-paper accepted to these prestigious conferences in 2025 or 2026. Sharing your track and overall assessment would be invaluable. Recent developments, like those detailed in "Prism accidentally leaked," highlight the complexities of the AI research pipeline.
Does anyone else miss the old conference ecosystem? [D]
The research community is reflecting on a shift in the conference landscape. Many recall a time when established events like BMVC, ACCV, FG, ICIP, and ICASSP fostered vibrant, specialized communities—FG for face analysis, ICASSP for signal processing, and the others for consistently strong papers. Now, with submission numbers surging and review processes strained, concerns arise about potentially overlooked research.
Looking for JEPA devil advocates [R]
The emergence of JEPA-like world models presents a compelling, future-focused direction for robot learning, as highlighted by recent research. While Yann LeCun’s vision is undeniably ambitious, a critical evaluation is warranted. We're seeking perspectives that challenge the current trajectory – "devil's advocates" who can identify potential downsides compared to alternative world model approaches. Are there overlooked limitations or vulnerabilities within JEPA’s framework? Explore this discussion, and consider “Are Current AI Memory Architectures Optimizing for the Wrong Abstraction?” for a deeper dive into related challenges.
whats the best and complete way to keep up with ai/ml news? [D]
Staying current in the rapidly evolving AI/ML landscape can feel overwhelming, especially when a single newsletter isn't enough. To ensure you're not left behind, prioritize a multi-faceted approach. Begin with curated aggregators and industry publications, then supplement with focused Twitter/X lists of leading researchers and practitioners. Finally, actively participate in relevant online communities. For deeper insights into related trends, explore our recent article, "Neil Rimer thinks the AI money is coming back out," which offers a valuable perspective on market dynamics.
TACL journal doubts [D]
Navigating the TACL review process can understandably generate questions. Submitting around June 1st for the July cycle suggests reviews may arrive within the subsequent weeks, though timelines can vary. Historically, the full TACL publication process takes several months. TACL holds considerable respect within the NLP community, viewed as a strong venue for impactful research. Its reputation reflects a rigorous review process and high publication standards. For those exploring related avenues, consider reviewing discussions around short-paper submissions at ACL/EMNLP/EACL, as detailed in a recent article.
How a former DeepMind researcher raised at a $300M pre-seed valuation before launching a product
Andrew Dai, a former DeepMind researcher with over a decade of experience shaping influential AI systems—including work that informed ChatGPT—is pioneering a new frontier: visual AI. He recently secured a remarkable $300 million pre-seed valuation before even launching his product, signaling immense confidence in this emerging field. Dai articulates a clear vision for how visual AI will transform data management. For further insights into the evolving landscape of AI, explore our recent article, "Google continues its renaming streak by turning NotebookLM to Gemini Notebook."
OpenAI researcher Miles Wang in talks to launch AI drug discovery startup valued at $2B
Prominent OpenAI researcher Miles Wang is reportedly in discussions to launch an AI-driven drug discovery startup, potentially valued at $2 billion. This signals significant investor confidence in applying artificial intelligence to accelerate breakthroughs within the life sciences. The anticipated venture aims to transform pharmaceutical research through innovative AI applications. For a deeper dive into advanced AI systems, explore our breakdown of the Claude Fable 5 system prompt. This development underscores the growing momentum of AI across diverse industries.