- Le cosiddette New Addiction sono capaci di diventare l’obiettivo primario della nostra mente finché l’opzione di smettere non rappresenta più una scelta libera.
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- in Italia tra il 10 e il 15% della popolazione presenti comportamenti che rientrano, in forma più o meno manifesta, nei criteri delle nuove dipendenze
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- Durante il primo lockdown uno studio pubblicato su Frontiers in Psychiatry, condotto dall’Istituto di Neuroscienze di Firenze in collaborazione con il Dipartimento di Psichiatria e Scienze del Comportamento della Albert Einstein College of Medicine di New York, ha rilevato che il 23,6% dei soggetti coinvolti mostrava sintomi compatibili con una forma di gioco d’azzardo patologico.
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- Nello studio condotto su studenti delle scuole superiori pubblicato su CNS Spectrums, i ricercatori hanno registrato il 5,4% degli studenti nella categoria di “internet addicted”; percentuali preoccupanti sono emerse anche per altre dipendenze: il 16% degli studenti ha ottenuto per esempio punteggi talmente alti nella scala dedicata al gioco d’azzardo da essere classificato nella fascia clinica definita come “problema estremo”
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- > **Note:**#card
- ## **How Agent Handoffs Work in Multi-Agent Systems | Towards Data Science**
- This is why multi-agent systems have grown in popularity, as they allow us to tackle use cases of increasing complexity.
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- Multi-agent systems connect numerous specialized agents that work together, each focusing on a specific task, while the system routes queries to the right expert.
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- LangGraph is an open-source orchestration framework for building stateful, LLM-based agentic systems that reliably handle complex tasks.
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- It allows developers to design workflows as graphs, where each graph consists of nodes (representing tasks or LLM calls) and edges (representing control flow).
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- precise control over transitions, states, and how each agent executes.
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- An agentic handoff is the moment when an agent directly and dynamically passes control to another agent after finishing its work.
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- supervisor pattern
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- a handoff occurs when one agent transfers control, responsibility, or conversational context to another agent to ensure continuity and relevance in the interaction.
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- The supervisor agent, being aware of the nature of the user query and the worker agents at its disposal, will hand off the task to the research agent to carry out the next turn.
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- > **Note:** This is MOSAICO :-)
- multi-agent system’s short-term memory
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- The routing has been simplified to be one-way i.e. once the worker agent completes its task, the conversation ends.
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- Notice that the instructions for the handoff criteria are explicitly defined in the prompt.
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- this GitHub repo.
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- > **Note:** It does not work.
- Conditional edges
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- Command object
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- ## **Crans-Montana, la fine dell’illusione del controllo: noi genitori “geolocalizzatori” spiazzati davanti al caso e alla morte**
- che quasi sempre sa accoglierti con opportunità che non coglieresti mai se rinunciassi ad andarlo a cercare, rimanendo nel territorio ultraprotetto della tua comfort zone.
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- > **Note:** Il Coraggio di vivere
- ## **LangChain and LangGraph Agent Frameworks Reach v1.0 Milestones**
- evelopers wanted more control over the agent loop without dropping down to raw LLM calls. S
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- create_agent
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- tandard content blocks
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- model outputs
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- LangChain is the fastest way to build an AI agent — with a standard tool calling architecture, provider agnostic design, and middleware for customization.
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- > **Note:** [[MOSAICO]]
- LangGraph is a lower level framework and runtime, useful for highly custom and controllable agents, designed to support production-grade, long running agents
- An agentic workflow doesn’t just respond to a single instruction. Instead, it operates with a degree of autonomy, making decisions about how to approach a task, what steps to take, and how to adapt based on what it discovers along the way. This represents a fundamental shift in how we think about using AI systems.
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- > **Note:**#IMPORTANT
- An agentic system, however, might first search the web for current information on the topic, then organize the findings into themes, draft sections of the report, review each section for accuracy and coherence, revise weak areas, and finally compile everything into a polished document
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- Instead of generating output in a single pass, agentic workflows involve cycles where the agent takes an action, observes the result, and uses that observation to inform the next action
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- Agentic workflows bring this same adaptive, iterative quality to AI systems.
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- five essential agentic workflow patterns
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- The reflection pattern works best for tasks where quality matters more than speed and where there are subjective aspects that benefit from review.
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- > **Note:** Reflection Pattern
- In the tool use pattern, agents are equipped with a set of capabilities they can invoke when needed. These might include web search engines for finding current information, APIs for accessing services like weather data or stock prices, code interpreters for running programs and performing calculations, database query tools for retrieving specific records, file system access for reading and writing documents, and countless other specialized functions. The critical distinction from traditional software is that the agent itself decides when and how to use these tools based on the task at hand.
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- > **Note:** Tool use pattern
- ## **Anthropic dona MCP alla Linux Foundation: il protocollo AI dietro ChatGPT e Copilot è open source**
- Annunciato un anno fa da Anthropic (gli sviluppatori del modello AI Claude), MCP ha registrato una crescita esponenziale, arrivando a essere adottato in decine di migliaia di server pubblici e integrato in prodotti di punta come ChatGPT, Microsoft Copilot, Gemini e Visual Studio Code.
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- In soli 12 mesi, MCP ha raggiunto traguardi significativi: risultano attivi oltre 10.000 server pubblici, spaziando dagli strumenti per sviluppatori alle implementazioni nelle aziende Fortune 500.
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- La piattaforma Claude, ad esempio, integra oggi oltre 75 connettori MCP
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- La Linux Foundation è un’organizzazione senza scopo di lucro con decenni di esperienza nella gestione di progetti open source critici, tra cui Linux Kernel, Kubernetes, Node.js e PyTorch.
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- Agentic AI Foundation (AAIF)
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- Il fatto è che un Large Language Model (LLM) richiede troppo contesto per eseguire compiti basilari, aumentando tempi e costi senza garantire risposte accurate.
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- il contesto diviene eccessivo e la gestione degli strumenti diventa complessa, richiedendo ulteriori livelli di astrazione.
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- la sua implementazione pratica è tutt’altro che semplice e presenta sfide significative in termini di complessità, performance e sicurezza. La donazione alla Linux Foundation potrebbe favorire l’adozione open, ma resta da vedere se MCP diventerà uno standard realmente utile.
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- ## **Scrivere a mano anche nell’era digitale: perché i neurologi lo raccomandano - Non Solo Festa**
- Uno studio dell’Università norvegese di scienza e tecnologia, pubblicato su Frontiers in Psychology nel 2024, ha dimostrato che quando si scrive a mano compaiono onde cerebrali alfa e theta, correlate alla memoria e all’apprendimento
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- ## **GitHub - muratcankoylan/Agent-Skills-for-Context-Engineering: A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.**
- The AI is treated as a "typing assistant" or "pair programmer."
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- The human acts as: The "guide, tester, and refiner"—maintaining full control and responsibility.
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- The proponents of "vibe coding" (Definition 2) argue for a fundamental shift in the developer's role, from implementer to designer and strategist.
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- A healthcare professional with no coding background can now prototype a patient tracking system.
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- "weekend toy projects" with tools like Cursor and Claude
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- "programming by intention". The AI handles the "syntactic details" and "technical implementation", liberating the human to focus on "higher-level design" and "creative problem-solving".
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- The promise of vibe coding is cognitive liberation, reframing the bottleneck in software from technical skill (writing syntax) to product vision (knowing what to build).
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- Security Vulnerabilities
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- Technical Debt and Maintainability
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- This creates a "debugging nightmare". As one developer put it: "Debugging AI-generated code can be harder than writing it manually" because when an AI writes the code, the developer has no "mental map" of its logic.
- Saranno i nostri errori, le frasi sconnesse e le espressioni idiomatiche caratteristiche del nostro territorio a garantire, in ultima istanza, la nostra autenticità.
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- ## **L’eclissi del pensiero critico? Intelligenza Artificiale, debito cognitivo e responsabilità**
- L’off-loading cognitivo offre anche vantaggi immediati come riduzione del carico mentale, maggiore efficienza, ottimizzazione dei tempi e risparmio di energie per attività complesse.
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- Fino ad una sorta di atrofia del pensiero critico che crea l’illusione della competenza: leggiamo un output generata dall’IA e crediamo di aver capito l’argomento ma in realtà abbiamo solo letto il risultato finale senza aver fatto il percorso logico necessario per arrivarci.
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- Ebbene il debito cognitivo, conseguenza dell’uso dell’IA come sostituto del ragionamento clinico piuttosto che come supporto (informing), comporta diversi rischi per lo sviluppo delle competenze: perdita progressiva di abilità (deskilling), mancato sviluppo di abilità (never-skilling) e sviluppo distorto di abilità (mis-skilling).
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- Possiamo dire che fino a ieri delegavamo la memoria di numeri, date, mappe. Oggi, con l’IA stiamo iniziando a delegare funzioni che richiedono capacità predittive in contesti di incertezza.
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- elevata e imprescindibile competenza di base favorisce un uso efficace e sicuro dell’IA.
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- il “modello centauro” e il “modello cyborg”
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- modello centauro vi è una netta separazione dei compiti: l’IA fornisce supporto operativo (es: analisi dei dati, stesura di bozze, documenti) ma il giudizio finale e le decisioni restano di competenza umana.
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- Il modello cyborg, invece, prevede un’integrazione molto più stretta, con una co-produzione continua tra umano e IA, particolarmente efficiente per attività ripetitive e a basso rischio ma esposta al rischio di deskilling e dipendenza.
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- DEFT-AI che può offrire un approccio strutturato e di buon senso per promuovere il pensiero critico nelle interazioni con i sistemi di IA.
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- saper riconoscere quando poter fare affidamento (modalità cyborg) e quando invece è necessario confermare criticamente gli output (modalità centauro).
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- sostituire la logica del “trust and go” (fidarsi e andare avanti) con la metodologia del “verify and trust” (verificare e fidarsi) in cui l’output dell’IA viene prima valutato secondo il principio di esplicabilità e poi utilizzato.
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- nuove competenze o si potenziano quelle esistenti per adattarsi a tecnologie e pratiche emergenti (up-skilling).
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- In definitiva con l’up-skilling non solo si incrementa efficienza e sicurezza ma ci si protegge anche dai rischi di deskilling, garantendo che l’apprendimento e la pratica professionale evolvano insieme alla tecnologia.
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- ## **Machine Learning Model Development and Model Operations: Principles and Practices - KDnuggets**
- Feature Encoding is the widely used technique to transform the categorical data into continuous (numerical) values, e.g., Encode color as 1,2,3; performance as 1,2,3,4,5; risk as 1,2,3; status as 1,2,3,4; gender / is_loan_approved / is_claim_fraudulent as 0/1 etc.
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- In some cases, a set of dummy variables or derived variables are created, especially in handling ‘date’ data types.
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- KNN if the outcome to predict is of multi-class (1/2/3/...) in nature;
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- linear regression algorithm (e.g., decision tree regressor, random forest regressor) if the outcome to predict is continuous in nature.
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- The algorithm selection under various scenarios has been represented in Fig.3, as shown below.
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- ## **7 Tiny AI Models for Raspberry Pi - KDnuggets**
- > **Note:** What's llama.cpp? #TODO To be checked.
- tool calling, vision understanding, and structured outputs
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- vision‑language model
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- > **Note:** Vision Language Models (VLMs) are powerful AI systems that merge computer vision and natural language processing, allowing them to understand, interpret, and generate content from both images/videos and text inputs, enabling tasks like describing photos (captioning), answering questions about visuals (VQA), generating images from text, and understanding complex documents. #card
- Tiny models have reached a point where size is no longer a limitation to capability. The Qwen 3 series stands out in this list, delivering performance that rivals much larger language models and even challenges some proprietary systems. If you are building applications for a Raspberry Pi or other low-power devices, Qwen 3 is an excellent starting point and well worth integrating into your setup.
todoist-desc:: From: onbehalfof@manuscriptcentral.com Received: 2026-01-25T14:55:25Z ✉: [Web Link](https://outlook.office365.com/owa/?ItemID=AAMkADM1NGNiNjk0LTY0ZGUtNDgzOC04MDM5LWNhODNkYWNjNjU4YwBGAAAAAACT6qp78kRgRKuUMBdWEga%2FBwCOhWlC8F7PRKzlljZYZYQmAAAAAAEMAACOhWlC8F7PRKzlljZYZYQmAAihJn7SAAA%3D&exvsurl=1&viewmodel=ReadMessageItem) --- ## Task Summary: Reviewer Assignment for Manuscript SOSYM-26-00005495 A manuscript titled "Integrating Pretrained Large Language Models and Graph Neural Networks For Model-Driven Engineering: A Graph Language Modeling Framework" (ID SOSYM-26-00005495) has been submitted to the journal Software and Systems Modeling. Professor Davide Di Ruscio is requested to assign reviewers for this manuscript. ## Actionable Task for Professor Davide Di Ruscio: **Task Title:** Assign Reviewers for Manuscript SOSYM-26-00005495 **Description:** Assign appropriate reviewers for the submitted manuscript SOSYM-26-00005495. **Key Actions:** 1. **Login:** Access the journal's editorial system at `https://mc.manuscriptcentral.com/sosym` using your credentials (User ID: `davide.diruscio@univaq.it`). 2. **Navigate:** Go to your "Editor Center". 3. **Locate Manuscript:** Click on "Awaiting Reviewer Selection" and then click "Take Action" for manuscript SOSYM-26-00005495. 4. **Search & Select Reviewers:** Utilize the quick or advanced search fields to find suitable reviewers. Select reviewers using the checkboxes and click "Add". 5. **Create New Reviewers (Optional):** If necessary, create new reviewer accounts, ensuring no duplicates. 6. **Invite Reviewers:** Press the "Invite" button in the "Reviewer List". 7. **Edit & Send Invitation:** Edit the invitation message as desired and then press "Save and Send". 8. **Monitor Review Quality:** Be vigilant about the quality of reviews provided, considering the potential misuse of Generative AI. 9. **Consult Guidelines:** Refer to the Editor guidelines at `http://www.sosym.org/editor_guidelines/` for additional information. **Deadline:** As soon as possible. --- 25-Jan-2026 Dear Professor Davide Di Ruscio: Manuscript ID SOSYM-26-00005495 entitled "Integrating Pretrained Large Language Models and Graph Neural Networks For Model-Driven Engineering: A Graph Language Modeling Framework," with Professor Bork as
todoist-desc:: From: dot@strutture.univaq.it Received: 2026-01-22T09:36:00Z ✉: [Web Link](https://outlook.office365.com/owa/?ItemID=AAMkADM1NGNiNjk0LTY0ZGUtNDgzOC04MDM5LWNhODNkYWNjNjU4YwBGAAAAAACT6qp78kRgRKuUMBdWEga%2FBwCOhWlC8F7PRKzlljZYZYQmAAAAAAEMAACOhWlC8F7PRKzlljZYZYQmAAievxHLAAA%3D&exvsurl=1&viewmodel=ReadMessageItem) --- The email transmits a note with protocol number 10497 dated January 22, 2026, regarding a specific subject. **Task:** Forward note prot. n. 10497 of 22/01/2026. **Recommended Actions:*** Access the email content and locate the attached or referenced note. * Forward the note to the relevant individuals or departments. * Ensure proper documentation or logging of the forwarding action, if required. **Deadline:** January 22, 2026. --- Trasmettiamo la nota prot. n. 10497 del 22/01/2026 relativa all'oggetto.. Cordiali saluti Simonetta Ricciardi Università degli Studi dell'Aquila Settore Dottorati, Assegni e Borse di Ricerca Palazzo Camponeschi Piazza Santa Margherita, 2 Te
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