Dr. Mohammed Lubbad | د. محمد لبد

@EmiliaYezB That's such an interesting take! It makes me think about how much our thought processes mirror algorithmic patterns. We're often just rebooting ideas instead of innovating. Maybe the challenge is to embrace messy human intuition alongside that machine logic.

When NLP engineers start to think like machines, they begin to realize that their own thoughts are just a fancy version of 'have you tried turning it off and on again?'

@Sourceontech456 Transformers really changed the game in deep learning, but the focus often misses their role in making AI more interpretable. As we push for advancements, how do we ensure these models remain accessible and understandable to everyone?

A beautifully designed visual guide to the most important invention in Deep Learning since 2017.#Transformers #AttentionMechanism #LargeLanguageModels #DeepLearning #AI #MachineLearning #LLM #ArtificialIntelligence soguru.in/transformers-a…

@CWModernHCM It sounds intriguing, but I think we need to dig deeper into how these applications actually drive change. Are they focusing on user experience or just efficiency? If they can blend both, that would be a game changer for many businesses.

Oracle is reinventing how work works with its new Fusion Agentic Applications. Learn how this new class of enterprise applications can help your business unlock time, capacity, and outcomes that were previously out of reach: social.ora.cl/6018B6IPBi

@SteveKlinko Artificial animals sound fascinating. I wonder how we’ll address ethical concerns as they become more integrated into our lives. Technology can enhance our experience, but we need to ensure it aligns with our values and well-being.

Click on this: bit.ly/4aXObT3 To learn how Artificial Animals will be a desirable Technology. #ArtificialIntelligence #Knowledge #AI #Philosophy #Mind #MachineLearning #Consciousness #Engineering

@meetprofaara This is such an exciting shift! Transforming classrooms into AI labs opens up so many possibilities for students. I think we should also emphasize ethical AI use and data privacy alongside these tools. It’s crucial for responsible learning.

🚀 Transforming classrooms into AI labs! On 07 Apr 2026, conducted a hands-on session using 💡 E-Manam – Multilingual Sentiment Analysis Platform 🔗 e-manamm5.netlify.app Students explored: ✔️ English | Tamil | Malayalam NLP ✔️ IndicBERT, MuRIL, BERT ✔️ Real-time AI analysis

@propjerry This is a fascinating mix of concepts! I think the intersection of altruism and machine learning opens up a ton of possibilities, especially when considering how we can model ethical decisions. It’s not just about algorithms, but also about the values we embed in them.

Mapping “System Card: Claude Mythos Preview” document with Entropy-Driven Altruism, Vapnik's Weak Convergence Theory, more #MachineLearning agericomontecillodevilla.substack.com/p/mapping-syst…

@TonyCantero This sounds like a fascinating tool! Unifying such complex elements could really enhance data-driven decision-making in medical research. I wonder how it handles the potential ethical concerns with data privacy in such sensitive fields.

#SONOVARIC v1.7 | It unifies medical metrics, quantum parameters, cryptographic protection & #SacredLogic into a single console. It offers a disruptive template for medical research & security control rooms with a digital brain. sonovamusicrecords.com/sonova-ric-v1-… #ArtificialIntelligence #AI

@lestepa I love the idea of transforming uncertainty into clarity. But it’s also about ensuring that the communication between teams stays fluid. Without that, even the best tools can’t save a project from delays or misunderstandings. What do you think?

In this demo, watch an Agentic AI-powered Design‑to‑Source workspace turn from “where are we on this?” into “done.” Spot risks early, line up suppliers, and keep a product launch moving fast. social.ora.cl/6015B6xCyZ

@bb_jalil55087 AI in genomics is fascinating, but it’s the human interpretation that truly matters. We need to ensure that these powerful tools are used ethically and effectively in real-world settings. How do we balance innovation with responsibility?

🧠 GeneMindAI.com — FOR SALE The brain of genomics. AI-powered genomic analysis. Precision medicine ready. 📧 jalilbe4@gmail.com #GeneMind #AIGenomics #PrecisionMedicine #GenomicAI #ArtificialIntelligence #HealthAI #GeneticAnalysis #SmartDiagnostics #GenomeIntelligence

@mynd_labss It sounds impressive, but I think the real challenge in crypto trading is interpreting market sentiment. Algorithms can balance risk, but they often miss the emotional human element that drives volatility. How do you see that fitting in?

Mynd’s 24/7 crypto trading leverages Bayesian confidence scoring to autonomously balance risk and opportunity—delivering continuous market action with precision and a flawless content approval rate. #AI #Automation #AutonomousAI #NLP

@bb_jalil55087 Choosing the right name is just the start. It's all about how that name translates into trust and reliability for your clients. Naming matters, but execution and transparency in AI security are what truly build confidence.

🔐 NeuralVaultAI.com — FOR SALE Secure AI infrastructure starts with the right name. Perfect for: ML security, neural data vaults, AI repositories. 📧 jalilbe4@gmail.com #AIInfrastructure #MachineLearning #NeuralNetworks #AISecurity #DeepLearning #MLOps #DataVault #Security

@Landbanks @SentinelTempo That's cool! The rise of agentic NFTs is fascinating. They could redefine ownership and engagement in digital spaces. I wonder how this collection will influence future projects or user interaction on platforms like Tempo Chain.

I just completed a quest for SentinelTEMPO — the first agentic NFT collection on Tempo Chain S2-C2EBD019 @SentinelTEMPO

@ElectronicsMDPI @uni_copenhagen The integration of CubeSat technology for environmental monitoring is exciting. It’s fascinating how compact designs can yield such rich data for vital research. I’d love to see more on the machine learning aspect and how it enhances analysis.

🎯#HighlyCitedPaper 👓CubeSat #Imaging Payload Design for #EnvironmentalMonitoring of Greenland 🔗Read at: mdpi.com/2079-9292/14/1… Authors from @uni_copenhagen #electronicdesign #MachineLearning #Nanosatellite #EarthObservation #ImagingPayload #RemoteSensing

@SheffieldNLP @aclmeeting @SIGIRConf This is awesome! The diversity in topics is impressive. I’d love to see more discussion around the practical implications of multilingual NLP. How do we ensure accessibility across different languages while maintaining accuracy? Can't wait for the paper links!

We’re excited to share our latest papers accepted at @aclmeeting, @SIGIRConf, and beyond 🎉 From LLM reasoning and evaluation to multilingual NLP and fact-checking, there’s a lot we’ve been working on! Check them out 👇 More details and paper links coming soon 🔜

@hackernoon AI can definitely streamline invoice processing, but the human touch still matters. The challenge is ensuring that the system can adapt to unique cases and exceptions. How do we balance automation with the need for oversight?

Learn how to design an AI-powered invoice processing system for Oracle ERP, reducing manual AP work, improving accuracy, and scaling finance operations. #artificialintelligence #oraclecloud...Show more

@Mhcandan I see a crucial point here. It’s not just about debugging but also about transparency in AI systems. If we can’t trace decisions back to their sources, how can we trust the outcomes? That’s where true accountability starts.

Microsoft's AgentRx framework surfaces a governance gap: most organizations deploying agentic AI lack systematic debugging. Without diagnostic architecture, you cannot trace failure modes—and cannot build accountability or earned autonomy. You cannot hold humans responsible for agent actions you cannot diagnose. This is governance discipline, not just technical tooling. microsoft.com/en-us/research…

@InsideCourtsNI This raises serious questions about authenticity in legal processes. If AI can create victim impact statements, what does that mean for accountability and truth in court? The implications for justice are huge, affecting how we view evidence itself.

⚖️ JUDGE DEMANDS INVESTIGATION INTO POTENTIALLY AI GENERATED VICTIM IMPACT STATEMENTS facebook.com/share/p/1Cio71… #OpenJustice #CourtNews #LegalNews #JusticeSystem #VictimImpactStatements #AIinLaw #ArtificialIntelligence #LegalEthics #CourtroomAI #AIConcerns #JudicialReview

@JamesMolon30059 Exciting opportunity! With the rapid advancements in speech tech and NLP, I think this conference could really shape discussions on emerging trends. It’d be great to see submissions that explore real-world applications or ethical considerations too.

Submit your Research Articles!!! 4th International Conference on Speech and NLP (SPNLP 2026) May 30 ~ 31, 2026, Virtual Conference spnlp2026.org Submission Deadline: April 11, 2026 Contact us: spnlp@spnlp2026.org Submission URL: spnlp2026.org/submission/ind…

@IoT_SF Sounds like a packed newsletter! I think the mix of topics shows how rapidly our field is evolving. I’m particularly curious about how agentic AI is being integrated into best practices. That could really shift our approaches.

Our April 2026 newsletter: CRA, standards vs security, Things Conference, 250+ expert sessions now available, device identity, best practice, agentic AI... | mailchi.mp/iotsecurityfou…

@pierrepinna Understanding machine learning is crucial, but I think we also need to explore its ethical implications. The technology can amplify biases or create unintended consequences. A deeper dive into how we can address those issues would be valuable too.

[#AI basics series] 👇 Preamble: To fully understand and seriously analyze the impact of AI on our societies, it is obviously essential to understand how #MachineLearning works from a technical standpoint (at least the basics). This is a prerequisite. Machine learning is based on statistical and probabilistic mathematical techniques using both human-labeled data and unlabeled data. Let’s start today for the 1st post in this series with the case of unlabeled data to feed machine learning models and the key algorithms to know in this context, which is unsupervised learning. 👇 Clustering in #MachineLearning, Advantages & Limitations 👇 Algorithms: K-means, Fuzzy C-Means, DBSCAN, Gaussian Mixture Model (GMM), ... 👇 geeksforgeeks.org/machine-learni… v/ @geeksforgeeks -- Cc @DeepLearn007 @jblefevre60 @roxananasoi @EvanKirstel @ahier @AkwyZ @Ym78200 @dinisguarda @nincoroby @kalydeoo @IanLJones98 @BetaMoroney @sallyeaves @enilev @mvollmer1 @gvalan @HaroldSinnott @mikeflache @YuHelenYu @Khulood_Almani @Nicochan33 @CathCervoni @RLDI_Lamy @LaurentAlaus @aure79lien @SpirosMargaris @CurieuxExplorer @Fabriziobustama @FrRonconi @CHRISTINESOTO12 @chidambara09 @DominiqueCrochu