research
research on Beyond Market Intelligence: a running collection of 72 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.
Startup ARR is less secure than ever, new research shows
Recent research confirms a concerning trend: startup ARR is facing unprecedented insecurity. The rapid shift to AI has fundamentally disrupted enterprise buying patterns, leaving many startups struggling to adapt. Traditional sales cycles are dissolving, demanding a new approach to securing recurring revenue. Explore how to navigate this evolving landscape and future-proof your business. For a deeper dive into optimizing LLM workflows, see our article, "Shopify Introduces Gisting." It’s time to embrace a future-focused strategy for sustainable growth.
Best place to rent an NVIDIA L40S GPU from India?[R]
Finding an NVIDIA L40S GPU in India presents unique challenges, particularly regarding cost and payment methods. Several avenues exist, ranging from local cloud services and hardware distributors to international providers. Prioritizing UPI payment support (GPay, PhonePe, Paytm) is key to avoiding costly international transaction fees. Researching rental rates and outright purchase prices across these options is crucial to securing the best deal. For deeper insights into leveraging AI for informed decision-making, consider exploring our article, "Beyond Point Predictions: A Practical Introduction to Bayesian Neural Networks."
Good Machine Learning Posters [D]
Preparing for ECCV 2026 and seeking inspiration for impactful machine learning poster design? You're in the right place. We've gathered a community discussion highlighting exceptional ML/CV posters—a valuable resource for crafting a compelling visual presentation of your work. To further enhance your understanding of current trends, explore our analysis of "Sliding-window attention beats linear on long-context reasoning," demonstrating practical solutions for optimizing large language models. Discover examples and strategies to elevate your poster and maximize its impact at the conference.
Is anyone esle going to ECCV and wants to get in a groupchat for socials? [D]
Heading to ECCV and seeking connection? This post highlights a common challenge: navigating a large conference when you're not part of a sizable team. One user is actively seeking others to connect with for informal socials and proposes a group chat to facilitate spontaneous gatherings. If you're in a similar situation and looking to expand your network at ECCV, reach out via DM!
*ACL Findings or TMLR? [D]
Navigating the conference publication landscape presents a strategic challenge. With NeurIPS appearing unlikely given current scores, the decision between Transactions on Machine Learning Research (TMLR) and *ACL Findings* warrants careful consideration. While both venues offer visibility, *ACL Findings* likely presents a higher probability of acceptance. Genuinely curious about industry perspectives: would you prioritize *ACL Findings* or TMLR on your publication record? For deeper insights into related AI discovery research, explore our article on "Autonomous Mathematical Discovery in an Open-World Multi-Agent Environment."
NeurIPS accepted papers leaked? [D]
A significant development has emerged: a GitHub repository containing approximately 7,000 papers, potentially representing the accepted submissions for NeurIPS 26, has surfaced. While some entries are anonymized, the level of detail suggests a high degree of accuracy. The early release raises questions about authenticity, and confirmation from the NeurIPS community is actively being sought. This situation highlights the increasing importance of responsible data handling and access. For further context on AI agent capabilities, explore our recent article, "You Never Told Your Agent What Done Means.
Best ML papers to pick up writing skills [D]
Sharpen your research writing with a curated selection of impactful Machine Learning papers. For PhD students and early researchers, mastering clear communication is paramount. We’ve compiled a list prioritizing papers that excel in explaining complex problems, methodology, and implementation details with accessible prose – particularly those post-2015 leveraging effective visuals. Consider exploring works from researchers known for their clarity, as strong writing significantly enhances impact. For further guidance on career pathways, see our related article, "PhD Internship in smaller lab [D]," which addresses internship advantages.
Google CS PhD Fellowship 2026 [R]
The Google CS PhD Fellowship 2026 [R] decision notifications are anticipated around August 31st for candidates primarily in North America, though updates may vary. This thread serves as a central hub for applicants to share their outcomes—approved or rejected—as they receive them. Early reports are welcome! For those exploring AI-assisted coding practices alongside their research, consider our guide, "How to Work with AI Coding Agents," for practical insights into maximizing code quality. We’ll continue to update this space as more information becomes available.
NeurIPS 2026 Acceptance Calculator [P]
Navigating NeurIPS submissions can feel daunting. To help demystify the process, we’ve developed a NeurIPS 2026 Acceptance Calculator [P], a small model estimating acceptance probability based on scores and a projected acceptance rate. Explore it here: https://levilingsch.github.io/neurips-acceptance-estimator/. This tool offers a practical way to assess your submission's potential. For researchers looking to bolster their writing skills alongside their technical contributions, our "Best ML papers to pick up writing skills [D]" article provides valuable guidance.
An Anthropic researcher just gave us a peek at self-improving AI
Recent advancements demonstrate the remarkable potential of self-improving AI. An Anthropic researcher recently showcased a system that successfully addressed ten distinct benchmarks for misaligned behaviors – achieving performance gains across all areas without compromising overall function. This signifies a crucial step toward safer and more reliable AI. Explore this progress and the broader landscape of AI development; for deeper insights into maximizing AI agent performance, see our article, "Connecting My LangGraph AI Agent to Postgres."
Travel and stay accommodation for EMNLP [D]
Congratulations on your EMNLP 2026 paper acceptance – a significant milestone for a PhD student! Securing travel and accommodation can be a challenge, particularly without departmental funding. Beyond the Diversity & Inclusion subsidies and volunteer opportunities you’ve already identified, explore broader AI conference grant databases like those maintained by AAAI and ACL. The D&I subsidies typically offer partial coverage; amounts vary, so review the EMNLP 2026 guidelines for specifics.
Does registering an abstract, not the full submission yet, count as a double submission? [D]
Navigating conference submission guidelines can be tricky. A common question arises: does registering an abstract—prior to the full paper submission—constitute a double submission? This query, posed by /u/obliviousphoenix2003, highlights a crucial point for researchers. To ensure compliance and avoid potential rejection, always verify the specific rules of the target conference. For example, as detailed in "Catching bugs in scikit-learn," meticulous attention to detail, even in underlying libraries, is essential for robust research.
Gamma acquires Accel-backed design startup Lica
Gamma expands its capabilities with the acquisition of Lica, a design startup previously backed by Accel. This strategic move integrates Lica’s expertise into Gamma's platform, with the co-founders joining our research team to pioneer new advancements. We're focused on empowering users with intuitive tools for knowledge creation and communication. This acquisition underscores Gamma’s commitment to innovation in the evolving landscape of content creation, mirroring the scale of acquisitions like Stripe’s recent purchase of OpenRouter.
Archival vs non archival workshop [R]
Understanding NeurIPS workshop archiving is crucial for maximizing the impact of your work, particularly for graduate school applications. A key distinction exists: NeurIPS workshops, like many others, are typically non-archival. Consequently, publication in a proceeding may carry less weight than a peer-reviewed journal. For context, consider how preprints and subsequent publications are handled—a discussion explored in our article, "How to cite/talk about preprint-subsequent works for a camera-ready version?". Prioritize venues that offer robust archival to strengthen your academic record.
AAAI 2027 Reviewer Bidding and Assignment Integrity [D]
Recent concerns regarding reviewer collusion at AAAI 2027, particularly within two-cycle review assignments, highlight a critical challenge in maintaining research integrity. The prevalence of submissions from a single geographic region increases the likelihood of these problematic pairings, potentially enabling unethical behavior.
acl arr august 2026 (desk rejected ) [D]
Experiencing a desk rejection from ACL citing prior review, despite never submitting the work, is understandably frustrating. It suggests a potential issue with reviewer records or a possible mix-up. While a definitive solution is challenging without further investigation, carefully review submission logs and consider contacting the ACL program chairs with detailed documentation of your submission history. This situation highlights the importance of understanding conference archival policies, as discussed in our related article, "Archival vs non archival workshop."
OpenAI Pays $280,000 For This Job. You Don't Have To Be An Engineer.
OpenAI recently made headlines, investing $280,000 in a role that didn't require engineering expertise. This highlights a significant shift: the demand for skilled prompt engineers and AI trainers is surging. It’s an accessible entry point into the AI landscape, emphasizing the power of clear communication and strategic instruction over traditional coding skills. Explore how you can leverage your analytical abilities to shape the future of AI—it’s a future-focused opportunity.
EMNLP 2026 Findings : worth attending in person?[D]
Congratulations on your first AI conference paper acceptance! The EMNLP 2026 Findings track presents valuable, rapidly evolving research—attending in person is highly recommended to maximize engagement with this dynamic work. While not mandatory, the in-person experience fosters crucial networking and deeper understanding of the presented findings. For those considering the financial aspects, see our related article, "EMNLP26 Cost," for a breakdown of student registration fees with an accepted paper. Prioritize experiencing the research firsthand; it's a significant milestone.
Epistemic Intelligence in Machine Learning Neurips Workshop page limit? [D]
Submitting to the 3rd Workshop on Epistemic Intelligence in Machine Learning at Neurips requires careful preparation. While the organizers have yet to confirm a specific page limit, historical precedent suggests two likely scenarios: either mirroring the ICML workshop's 6-page limit or aligning with the main Neurips conference’s 9-page constraint. To ensure your paper meets submission guidelines, we recommend erring on the side of brevity. For further exploration of related topics, consider our recent analysis of EMNLP 26 cost considerations.
US government lab is probing Chinese lidar for security vulnerabilities
Idaho National Laboratory is conducting a critical security review of Chinese-manufactured lidar systems, a move funded by the electric and autonomous vehicle sectors. This probe seeks to identify potential vulnerabilities that could impact vehicle safety and data integrity. The assessment underscores growing concerns about the security of increasingly integrated automotive technologies. This follows similar scrutiny of other critical components, highlighting the need for robust security evaluations.
Discussion thread for EMNLP 2026 Notifications/Results [D]
EMNLP 2026 notifications and results are expected to be released today – wishing everyone the best as they gather in Budapest! This thread serves as a central hub for discussion surrounding these announcements. We anticipate a lively exchange as the community processes the outcomes. For context, recent developments in AI integration with spreadsheet tools are impacting workflows; for example, Microsoft is retiring the COPILOT function in Excel. Explore the thread for updates and share your insights.
ICLR numbered citations possible? [R]
Navigating citation formatting for ICLR submissions can be a critical detail. The instructions specify Author Year format, but a shift to numbered citations (without spaces) risks immediate desk rejection. While community experience on this is valuable, definitive guidance remains scarce. Submitting with a non-compliant format introduces unnecessary risk. For further context on navigating conference deadlines and related considerations, explore our article, "NeurIPS 2026 Author Notifications Close to ICLR Deadline." Prioritize adherence to the provided guidelines to ensure your submission’s review.
If you had a bunch of GPUs lying around, what would you actually build with them? (Running LLMs is off the table) [D]
Beyond the well-trodden path of local LLMs, a stack of high-end GPUs unlocks a realm of compelling possibilities. What truly innovative projects would emerge? Consider distributed simulations, specialized generative models outside of text, or accelerated rendering pipelines. The opportunity exists for impactful homelab experiments demanding serious computational power, or even uniquely ambitious personal endeavors. Explore the potential – as demonstrated by projects like the Doom renderer reimagined as a transformer, discussed in "I compiled Doom's renderer into a 21B-parameter transformer"—and share your most intriguing ideas.
How much does adding an honest limitations section hurt the paper? [D]
Addressing limitations honestly in research papers—while generally beneficial—raises critical questions about reviewer bias and potential requests for remediation. Does openly acknowledging constraints negatively impact perception, or will reviewers demand fixes outlined in the limitations section? Furthermore, the introduction of AI reviewers introduces a novel consideration: could these limitations inadvertently bias algorithmic assessment? Exploring these nuances, as discussed in "My Model Was Cheating on Its Own Test," highlights the complexities of transparency in AI research.