AI News Archive: June 7, 2026 — Part 4
Sourced from 500+ daily AI sources, scored by relevance.
- Multi-level, multi-body atomic interaction graphs for machine learning-based prediction of protein-ligand binding energies
Accurate prediction of binding affinity is crucial for rational drug design and discovery. Traditional computational methods often rely on complex scoring functions that incorporate a multitude of physical and chemical descriptors, leading to high computational demands and sometimes limited generalizability. In this work, we propose a novel scoring function that models multi-level, multi-body atomic interactions using graph-based representations. Our method constructs comprehensive interaction graphs that incorporate both pairwise and triplet-wise atomic features that help capture cooperative spatial patterns essential for binding affinity prediction. By employing a feature fusion strategy, GMI-Score maintains model simplicity while enhancing accuracy. Extensive evaluation across multiple datasets, such as PDBbind v2013, PDBbind v2016, PDBbind v2020, CSAR-NRC-HiQ, and PDBbind-Redocked, demonstrates that our model consistently outperforms state-of-the-art scoring functions, achieving Pearson correlation coefficients up to 0.877. Furthermore, it retains strong predictive power under strict data leakage controls and realistic docking conditions to highlight its robustness and generalizability.
- Single-cell gene regulatory network reconstruction and key regulator identification using a dual-channel fusion graph convolutional network
Background and objective: Gene regulatory networks are formed by complex regulatory relationships between transcription factors and their target genes. A systematic understanding of these regulatory relationships is crucial for deciphering the molecular mechanisms that underlie cell state transitions under physiological and pathological conditions. Single-cell expression data can reveal cell-type-specific transcriptional regulation, and computational methods have recently been developed to infer gene regulatory networks from single-cell transcriptomics and prior regulatory knowledge. However, existing methods could not explore the common and specific information in expression correlations and prior regulatory knowledge, which can adversely affect prediction performance. Methods: We propose a novel method for inferring gene regulatory networks from single-cell RNA sequencing data. The proposed method consists of dual-channel graph neural networks and a weight-shared common graph neural network, enabling effective fusion of prior regulatory knowledge with gene co-expression patterns. Furthermore, we formulate a new computational framework built upon the proposed algorithm, which integrates differential gene expression profiles and regulatory changes to identify key regulators that distinguish different cell states. Results: Experimental results demonstrate that our method significantly improves the accuracy of regulatory inference across multiple datasets, outperforming other state-of-the-art approaches. Our method also exhibits robustness to noise and missing data. Analysis of two single-cell expression datasets suggests that the proposed framework could help identify key regulators involved in tumor metastasis and drug resistance. Conclusion: These results indicate that the proposed method could advance the understanding of the biological mechanisms underlying diseases by reconstructing single-cell gene regulatory networks and identifying key regulators across different cell states.
- CytoGem-XAI:A Hypergraph Neural Network Framework for Genome-Scale Metabolic Modeling and Interpretable Analysis
Genome-scale metabolic models are essential for understanding cellular metabolism, yet existing deep learning approaches remain black boxes, and traditional flux balance analysis (FBA) cannot provide sample-specific predictions. To our knowledge, CytoGem-XAI is the first framework to combine hypergraph neural network representation with interpretable, FBA-parallel analysis and sample-specific metabolic characterization. Built upon hypergraph representations where reactions are encoded as hyperedges connecting their participating metabolites, CytoGem-XAI introduces three analysis modules: perturbation-based carbon source importance ranking, hard intervention reaction bottleneck identification, and pathway-level topological attribution. Beyond prediction, CytoGem-XAI uniquely enables condition-dependent carbon source essentiality and reaction bottlenecks that vary with genetic background - capabilities absent from both traditional FBA and existing deep learning methods. Trained on 17,400 E.coli growth conditions using 10-fold cross-validation, our framework achieves 2 =0 .862,substantially outperforming AMN (R^2=0 .81,+6 .4%), FBA ( R^2=0 .62,+39%),and gradient boosting baselines (R^2 =0.71,+21%). Biological validation confirms that CytoGem-XAI identifies known essential carbon sources (e.g., alanine, malate) and rate-limiting enzymes (e.g., TCA cycle), while also revealing N-acetylmuramate - a peptidoglycan precursor - as a previously underappreciated essential nutrient.
- Polynomial Trajectory Compression for Protein Language Model Embeddings
Protein language models (PLMs) generate rich, layer-wise embeddings that capture diverse biological information but are expensive in terms of storage and computation at scale. In this work, we propose a compact surrogate representation for PLM embeddings across transformer layers using low-dimensional PCA projections and cubic polynomial trajectories. This approach enables efficient storage and on-demand reconstruction of these protein-level embeddings at any layer without rerunning the PLM. We evaluate our method on two downstream tasks: protein protein interaction and subcellular localization using ESM-35M and ESM-3B PLM. We show that the surrogate embeddings achieve high reconstruction fidelity while reducing storage and computational requirements significantly. The new approach also retains downstream task prediction performance compared to original embeddings. Our approach provides a scalable and practical solution for large-scale protein embedding storage and reuse.
- An Automated Wireless Seesaw System Enabling Spatial Separation of Action and Reward in Group-Housed Marmosets
Cooperation in social species is shaped by ongoing social relationships, partner choice, and group interactions, demanding experimental systems that preserve the social context in which these behaviors unfold. Here we introduce the e-Seesaw, a wireless system for automated liquid reward delivery designed to support home-enclosure experiments on reward access distribution in common marmosets (Callithrix jacchus) with minimal human intervention. The apparatus combines a modular peristaltic pump with a Bluetooth-controlled trigger, allowing spatial separation between the site of action and the site of reward delivery while preserving group housing. We provide detailed design files, software, and assembly instructions to support reproduction and adaptation. In a proof-of-concept deployment across seven families, animals readily engaged with the device, producing a median of ~87 trigger activations per session. Engagement was concentrated early within sessions and remained largely stable across repeated deployments, including under increased action-reward separation. These results established the e-Seesaw as a flexible and reproducible platform for automated reward-delivery experiments in animals tested within their social groups, while reducing human involvement and avoiding fixed dyadic testing.
- CiliAI: Automated segmentation and compartment specific fluorescence quantification of primary cilia in confocal microscopy images
Primary cilia regulate essential signalling pathways controlling cell proliferation, differentiation, and tissue homeostasis. Quantitative analysis of ciliary morphology and compartment-specific protein localization by confocal microscopy is labor-intensive, user-dependent, and difficult to scale, particularly for multiplexed 3D image datasets. Here, we present CiliAI, a web-based deep-learning workflow for automated detection, substructure segmentation, and quantitative analysis of primary cilia in confocal microscopy images. CiliAI identifies ciliary substructures including the basal body, transition zone, and axoneme from multiplexed 3D image stacks and performs automated measurements of cilium length and compartment-specific fluorescence intensity. In NIH-3T3 cells, automated cilium length measurements showed close agreement with manual quantification and no statistically significant difference between methods (mean difference -0.214 {gamma}m, p = 0.213). Automated fluorescence analysis reproduced previously reported reductions in transition zone-associated Cep290 signal intensity in Rpgrip1l-deficient cells and identified the absence of significant Rpgrip1l accumulation changes in Rmnd5a-deficient cells. Automated processing reduced analysis time from days of manual quantification to minutes. Together, these findings establish CiliAI as an automated framework for quantitative analysis of ciliary morphology and compartment-specific protein abundance in confocal microscopy datasets.
- OpenAI plots biggest ChatGPT overhaul since launch
$850bn start-up to recast hit chatbot as a route to higher-margin products before a potential IPO
- Trump signs memo putting ‘most advanced AI’ into military hands and banning vendors from pulling the plug
President Trump signed a national security presidential memorandum on Friday ordering the US military and intelligence agencies to accelerate their adoption of cutting-edge AI. The directive, NSPM-11, establishes a framework for “rapid onboarding of the most advanced AI models from multiple vendors.” It also bars any company from disabling, degrading, or modifying an AI system […] This story continues at The Next Web
- SpaceX inks $30 billion deal to provide Google with AI computing power
SpaceX inks $30 billion deal to provide Google with AI computing power
- Trump Administration in Talks for Direct Government Stake in OpenAI
Trump admin discusses taking US government equity stake in OpenAI
- The Mythos Race: Trump’s New EO and Glasswing’s Expansion
A roundup of headline AI developments from this past week is warranted, as fast-moving decisions from the White House to Anthropic demand immediate attention. Plus, a look at what may be the AI metric that matters most.
- Inside Apple’s Secret Meeting That Led It to Finally Take AI Seriously
Also: What to expect at WWDC 2026.
- Getting AI to sniff out Alzheimer’s early
Bengaluru startup is developing an affordable platform for dementia diagnostics
- OpenAI is still working on that ‘super app’
"Chat is dead" — at least, according to a senior OpenAI employee.
- OpenAI's Lockdown Mode Locks Down ChatGPT Against Prompt Injection Attacks
OpenAI introduces Lockdown Mode to protect ChatGPT from prompt injection attacks
- Nvidia clinches deals with South Korean giants include SK Group to advance AI boom
Nvidia clinches deals with South Korean giants include SK Group to advance AI boom Reuters
- SK Telecom and NVIDIA Build AI Infrastructure to Power Korea’s AI Innovation
NVIDIA and SK Telecom today announced that SK Telecom plans to build a gigawatt-scale AI Cloud in Korea using the NVIDIA DSX™ platform, with the first AI factory coming online in 2027.
- NVIDIA and SK hynix Announce Multiyear Technology Partnership to Advance Memory for AI Factories
NVIDIA and SK hynix today announced a multiyear technology partnership to advance next-generation memory for the global AI factory buildout and accelerate semiconductor design and manufacturing.
- NAVER Expands AI Infrastructure With NVIDIA to Serve Surging Global AI Demand
NVIDIA and NAVER today announced that NAVER will expand sovereign AI infrastructure, starting at 55 megawatts with plans to move to gigawatt scale using the NVIDIA DSX™ platform to rapidly design, build and scale full-stack, end-to-end AI platforms that can serve enterprises, industries and government.
- Nvidia taps Naver for gigawatt-scale AI cloud push in Korea
Nvidia and Naver are expanding their artificial intelligence infrastructure partnership and sovereign AI initiative, using the Korean internet giant’s existing data center in Sejong as the starting point to scale AI cloud capacity toward gigawatt-level AI factories. Nvidia said in a media prebriefing early Monday that it will work with Naver across its full AI stack, from DSX-based AI factories to Nemotron-powered sovereign AI models and Cosmos-enabled physical AI, as the US chip giant seeks to
- OpenAI plans ChatGPT 'superapp' overhaul ahead of listing, FT reports
OpenAI plans ChatGPT 'superapp' overhaul ahead of listing, FT reports Reuters
- OpenAI readies ‘superapp’ pivot ahead of planned IPO, FT reports
OpenAI readies ‘superapp’ pivot ahead of planned IPO, FT reports Fortune
- ChatGPT is no longer OpenAI's most important product. Here's why.
ChatGPT is no longer OpenAI's most important product. Here's why. Business Insider
- ‘Chat is dead’: OpenAI plans biggest ChatGPT overhaul ahead of IPO, pivots to AI agents, says report
OpenAI is planning a major overhaul of ChatGPT with the aim transforming the chatbot into a superapp that integrates AI agents, coding tools, and third-party services.
- Why OpenAI is disabling ChatGPT web access to fight prompt injection attacks
OpenAI has introduced Lockdown Mode for ChatGPT to improve security against prompt injection attacks.
- OpenAI plans ChatGPT 'superapp' overhaul ahead of listing: Report
The changes are part of a broader reorganisation at OpenAI, as it shifts resources to target lucrative enterprise clients and intensify competition with rival Anthropic
- OpenAI says "chat is dead" and plans to rebuild ChatGPT as a full-blown agent app
OpenAI is planning the biggest overhaul of ChatGPT since its launch. The chatbot will become a "superapp" bundling coding tools, AI agents, and partner apps like Canva and Booking.com. "Chat is dead," the company says internally. The future supposedly belongs to agents that handle tasks on their own. The article OpenAI says "chat is dead" and plans to rebuild ChatGPT as a full-blown agent app appeared first on The Decoder .
- ChatGPT's new Lockdown Mode lets you disable web access and more to protect sensitive data from prompt injection
OpenAI's new Lockdown Mode for ChatGPT disables web access, Deep Research, and Agent Mode to make data theft through prompt injection attacks harder. The mode doesn't fully prevent such attacks, it only blocks the final step in an exfiltration chain. Prompt injection remains an unsolved problem. The article ChatGPT's new Lockdown Mode lets you disable web access and more to protect sensitive data from prompt injection appeared first on The Decoder .
- OpenAI adds Lockdown Mode to ChatGPT to block data theft from prompt injection attacks
OpenAI has begun rolling out Lockdown Mode to ChatGPT, a new security setting designed to block attackers from stealing data through prompt injection attacks. The feature disables live web browsing, agent mode, deep research, image retrieval, Canvas networking, and file downloads. It is available to logged-in users across Free, Go, Plus, Pro, and self-serve ChatGPT […] This story continues at The Next Web
- ‘Chat Is Dead’: OpenAI Reportedly Planning Radical Changes to ChatGPT
It’s not the first time OpenAI has hinted at something like this.
- OpenAI Announces Unnerving New ChatGPT Feature Named ‘Lockdown Mode’
"Lockdown Mode is not intended for everyone," OpenAI's blog post says. In other words, you're probably not important enough.
- OpenAI reportedly has a major ChatGPT overhaul in store
The revamped AI tool will roll out in the coming weeks, according to The Financial Times.
- OpenAI’s planned ‘superapp’ gets closer as one employee says ‘chat is dead’
OpenAI Group PBC is still focused on its plans to transform ChatGPT into some kind of “superapp,” and it will have a heavy focus on artificial intelligence agents and autonomous coding bots, according to a new report in the Financial Times this weekend. By launching a superapp, the company hopes to be able to better […] The post OpenAI’s planned ‘superapp’ gets closer as one employee says ‘chat is dead’ appeared first on SiliconANGLE .
- Nvidia, SK to detail cooperation plan as Huang flags prolonged chip shortage
A SK Hynix spokesperson said group Chairman Chey Tae-won and Nvidia CEO Jensen Huang plan to brief the media on Monday morning, confirming a report by Newsis.
- Sorry, I’m not available. Talk to my AI double
Sorry, I’m not available. Talk to my AI double The Straits Times
- Top Trump artificial intelligence adviser to leave the White House
Top Trump artificial intelligence adviser to leave the White House The Washington Post
- Top White House AI Advisor to Leave Post
Top White House AI Advisor to Leave Post The Information
- Can AI detect smuggled sea cucumbers?
In a new study, an AI tool identified images of seahorse, shark fin and sea cucumber samples in luggage
- iOS 27 arriving tomorrow: Compatible devices, Siri's big AI updates and expected features
Apple's WWDC 2026 will take place on June 8, marking Tim Cook's last official event as CEO.The new update is expected to bring a revamped Siri, AI features in the Photos app, a redesigned Camera app, and easier shortcut creation via Siri
- At Build 2026, Microsoft Sent a Clear Message: Copilot+ PCs No Longer Matter
At Build 2026, Microsoft Sent a Clear Message: Copilot+ PCs No Longer Matter PCMag Australia
- At Build 2026, Microsoft Sent a Clear Message: Copilot+ PCs No Longer Matter
At Build 2026, Microsoft Sent a Clear Message: Copilot+ PCs No Longer Matter PCMag UK
- Can Google's Gemini Make You More Productive? I'm Living Proof That It Can
Can Google's Gemini Make You More Productive? I'm Living Proof That It Can PCMag Australia
- Starmer to unveil artificial intelligence plan to help jobseekers find work
An AI ‘bootcamp scheme’ will be rolled out across England over the summer
- AI helping build better AI: How agents accelerate Liger Kernel engineering
How agents accelerate Liger Kernel engineering with AI
- Europe opening up to self-driving taxis
Self-driving taxis, already booming in the United States and China, are emerging in Europe, with major companies launching trials this year in several capitals and the European Union set to step on the accelerator Monday.
- Dreambeans by Google Labs
Daily AI stories personalised from your Google apps
- FactGuard
Real-time AI fact-checking to fight fake news 🛡️
- NAADI
Corporation tax automated. So accountants advise, not admin
- SeaVid AI
ai video generator
- Fridgesnapai.recipes
Fridgesnapai.recipes