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  • Dock Traffic Light

    DockTechnik offer a range of Loading Bay Lighting including Loading Bay Traffic Lights. Our Services include Loading Bay Traffic Lights Service, Repairs, Sales and Design.

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  • Healthcare demands technology that is precise, secure, and highly reliable. Modern healthcare systems handle sensitive patient data while supporting real-time services like telemedicine and hospital operations, making scalability and performance essential. MERN and MEAN stack architecture provides a unified JavaScript ecosystem that simplifies full stack development, accelerates deployment, and ensures consistent user experiences. With non-blocking operations, strong security layers, and flexible data handling, these stacks support patient portals, EHR systems, analytics, and workflow automation. Justtry Technologies applies this approach to deliver secure, scalable, and user-friendly healthcare applications that balance innovation with responsibility.

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    Healthcare demands technology that is precise, secure, and highly reliable. Modern healthcare systems handle sensitive patient data while supporting real-time services like telemedicine and hospital operations, making scalability and performance essential. MERN and MEAN stack architecture provides a unified JavaScript ecosystem that simplifies full stack development, accelerates deployment, and ensures consistent user experiences. With non-blocking operations, strong security layers, and flexible data handling, these stacks support patient portals, EHR systems, analytics, and workflow automation. Justtry Technologies applies this approach to deliver secure, scalable, and user-friendly healthcare applications that balance innovation with responsibility. Visit: https://justtrytech.com/mean-and-mern-full-stack-development/ WhatsApp: https://wa.me/919500139200 Email ID: sales@justtrytech.com
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  • The Future of Location-Based Marketing in B2B: What Marketers Must Prepare For

    In an increasingly digital and data-driven world, location-based marketing is no longer just a consumer-focused tactic reserved for retail or mobile apps. B2B marketers are now recognizing the strategic value of location intelligence to reach high-value accounts, enhance personalization, and drive revenue growth. As we look to the future, location-based marketing in B2B is poised to evolve rapidly — and marketers must prepare to adapt. Here’s what’s coming next and how B2B teams can stay ahead.

    Why Location-Based Marketing Matters in B2B

    At its core, location-based marketing leverages geographic data to deliver relevant messaging or insights based on where a target audience is — whether that’s a specific company headquarters, an industrial park, or attendees at a trade show. For B2B marketers, this intelligence provides a competitive edge by allowing them to prioritize outreach based on physical context, optimize field sales efforts, and tailor content to localized pain points.

    Traditionally, location-based strategies in B2B have focused on event targeting, trade show geofencing, and market segmentation by region. But as technology advances and data becomes richer and more precise, the applications are expanding.

    1. More Precise Geofencing and Hyperlocal Targeting

    In the next few years, B2B marketers will leverage increasingly precise geofencing capabilities powered by AI and improved location data sources. Rather than broad targeting around a city or region, marketers will be able to zero in on specific corporate campuses, office floors, or even particular business units.

    This hyperlocal precision will enable more relevant outreach. For example, a software vendor could target decision-makers on the day of a major industry conference, delivering tailored ads tied directly to the event — a strategy that boosts engagement and shortens sales cycles.

    2. Integrating Location With Intent and Engagement Data

    Location data will begin to play a more integrated role in account insights and intent models. Today, many B2B platforms incorporate online behaviors — such as content downloads or search patterns — as signals of intent. Tomorrow, physical behaviors like repeated visits to certain business districts or attendance at industry events could become key intent indicators.

    Imagine combining CRM engagement metrics with anonymous location signals to determine which accounts are actively researching solutions at trade shows or competitive venues. This enriched insight gives sales and marketing teams a more holistic view of where accounts are in the buyer journey.

    3. Location-Based Personalization at Scale

    Personalization has been a longstanding priority for B2B marketers, but most personalization efforts today focus on digital behavior. What’s emerging is the ability to personalize content and messaging based on physical context. Location-aware content may adapt not just to industry or persona, but to where a prospect is located — such as custom messaging for prospects at industry hubs, near field sales offices, or within key markets exhibiting strong growth.
    This shift will require content strategies that incorporate localized themes and value propositions tied to specific regions or business ecosystems.

    4. Ethical and Privacy-Centric Practices

    With the growing use of precise location data comes heightened concerns around privacy and compliance. Regulations like GDPR and CCPA have already shaped how marketers manage personal data, but location tracking introduces new sensitivities.
    B2B marketers must adopt transparent data practices, obtain appropriate consent, and prioritize first-party data collection. Investing in privacy-centric location technologies that anonymize data and respect user preferences will build trust and mitigate legal risks.

    Preparing for What’s Next

    To succeed in the future of location-based marketing, B2B marketers should:
    • Invest in advanced location intelligence tools that integrate with CRM and marketing automation platforms.
    • Experiment with event-based geofencing to capture high-intent buyers in real-world environments.
    • Enhance personalization strategies with localized messaging and contextual relevance.
    • Prioritize ethical data practices to maintain compliance and customer trust.

    Location-based marketing in B2B is evolving from a tactical add-on to a strategic differentiator. Marketers who embrace this shift today will be better positioned to connect with buyers in meaningful, contextually relevant ways — driving stronger engagement and faster wins in the years ahead.

    Read More: https://intentamplify.com/blog/types-of-location-based-marketing-a-complete-guide-for-b2b-marketers/



    The Future of Location-Based Marketing in B2B: What Marketers Must Prepare For In an increasingly digital and data-driven world, location-based marketing is no longer just a consumer-focused tactic reserved for retail or mobile apps. B2B marketers are now recognizing the strategic value of location intelligence to reach high-value accounts, enhance personalization, and drive revenue growth. As we look to the future, location-based marketing in B2B is poised to evolve rapidly — and marketers must prepare to adapt. Here’s what’s coming next and how B2B teams can stay ahead. Why Location-Based Marketing Matters in B2B At its core, location-based marketing leverages geographic data to deliver relevant messaging or insights based on where a target audience is — whether that’s a specific company headquarters, an industrial park, or attendees at a trade show. For B2B marketers, this intelligence provides a competitive edge by allowing them to prioritize outreach based on physical context, optimize field sales efforts, and tailor content to localized pain points. Traditionally, location-based strategies in B2B have focused on event targeting, trade show geofencing, and market segmentation by region. But as technology advances and data becomes richer and more precise, the applications are expanding. 1. More Precise Geofencing and Hyperlocal Targeting In the next few years, B2B marketers will leverage increasingly precise geofencing capabilities powered by AI and improved location data sources. Rather than broad targeting around a city or region, marketers will be able to zero in on specific corporate campuses, office floors, or even particular business units. This hyperlocal precision will enable more relevant outreach. For example, a software vendor could target decision-makers on the day of a major industry conference, delivering tailored ads tied directly to the event — a strategy that boosts engagement and shortens sales cycles. 2. Integrating Location With Intent and Engagement Data Location data will begin to play a more integrated role in account insights and intent models. Today, many B2B platforms incorporate online behaviors — such as content downloads or search patterns — as signals of intent. Tomorrow, physical behaviors like repeated visits to certain business districts or attendance at industry events could become key intent indicators. Imagine combining CRM engagement metrics with anonymous location signals to determine which accounts are actively researching solutions at trade shows or competitive venues. This enriched insight gives sales and marketing teams a more holistic view of where accounts are in the buyer journey. 3. Location-Based Personalization at Scale Personalization has been a longstanding priority for B2B marketers, but most personalization efforts today focus on digital behavior. What’s emerging is the ability to personalize content and messaging based on physical context. Location-aware content may adapt not just to industry or persona, but to where a prospect is located — such as custom messaging for prospects at industry hubs, near field sales offices, or within key markets exhibiting strong growth. This shift will require content strategies that incorporate localized themes and value propositions tied to specific regions or business ecosystems. 4. Ethical and Privacy-Centric Practices With the growing use of precise location data comes heightened concerns around privacy and compliance. Regulations like GDPR and CCPA have already shaped how marketers manage personal data, but location tracking introduces new sensitivities. B2B marketers must adopt transparent data practices, obtain appropriate consent, and prioritize first-party data collection. Investing in privacy-centric location technologies that anonymize data and respect user preferences will build trust and mitigate legal risks. Preparing for What’s Next To succeed in the future of location-based marketing, B2B marketers should: • Invest in advanced location intelligence tools that integrate with CRM and marketing automation platforms. • Experiment with event-based geofencing to capture high-intent buyers in real-world environments. • Enhance personalization strategies with localized messaging and contextual relevance. • Prioritize ethical data practices to maintain compliance and customer trust. Location-based marketing in B2B is evolving from a tactical add-on to a strategic differentiator. Marketers who embrace this shift today will be better positioned to connect with buyers in meaningful, contextually relevant ways — driving stronger engagement and faster wins in the years ahead. Read More: https://intentamplify.com/blog/types-of-location-based-marketing-a-complete-guide-for-b2b-marketers/
    0 Kommentare 0 Geteilt 291 Ansichten

  • How AI-Driven Intent Data Is Transforming B2B Lead Generation in 2026

    B2B lead generation is undergoing a fundamental shift. Traditional models built on cold outreach, static buyer personas, and volume-based campaigns are rapidly losing effectiveness. In their place, a smarter, more precise approach is emerging—one powered by artificial intelligence and intent data. By 2026, AI-driven intent intelligence is not just enhancing lead generation; it is redefining how B2B organizations identify, engage, and convert buyers.

    From Lead Volume to Buying Signals

    For years, B2B marketing success was measured by the number of leads generated. But high volumes rarely translated into high-quality opportunities. Today’s buyers conduct most of their research independently—reading blogs, comparing vendors, joining webinars, and engaging in online communities long before filling out a form.
    AI-driven intent data captures these digital footprints and transforms them into actionable buying signals. Rather than guessing who might be interested, organizations can now see which accounts are actively researching specific solutions, which topics they care about, and where they are in the buying journey. This marks a critical shift from lead accumulation to buyer readiness.

    How AI Makes Intent Data Truly Actionable

    Intent data alone isn’t new. What’s changed is AI’s ability to analyze massive volumes of behavioral, contextual, and firmographic data in real time. Modern AI engines correlate website activity, content consumption, search behavior, social engagement, and third-party data sources to build dynamic intent profiles.

    By 2026, these systems can identify patterns humans can’t—predicting purchase likelihood, detecting early-stage research behavior, and continuously refining account prioritization. Instead of static scoring models, B2B teams now operate with living intelligence models that adapt as buyer behavior evolves.
    This allows sales and marketing teams to focus their efforts on accounts showing genuine buying momentum, dramatically increasing efficiency and conversion rates.

    Precision Targeting and Hyper-Personalization

    One of the most powerful impacts of AI-driven intent data is the ability to personalize engagement at scale. When AI understands not only who a buyer is but what problems they are actively trying to solve, messaging becomes instantly more relevant.

    Marketing teams can automatically tailor campaigns based on real-time interests—serving cybersecurity content to accounts researching breach prevention or ROI-driven messaging to executives evaluating vendors. Sales teams receive insights into pain points, competitive research, and timing signals, enabling outreach that feels helpful rather than intrusive.

    The result is a shift from disruptive marketing to contextual engagement—meeting buyers exactly where they are.

    Shorter Sales Cycles, Stronger Pipelines

    AI-powered intent intelligence also compresses sales cycles. By engaging prospects earlier and with greater relevance, organizations influence decisions before competitors even know a deal exists. Lead qualification becomes predictive rather than reactive, allowing teams to forecast pipeline with greater confidence.

    In 2026, high-performing B2B organizations no longer treat intent data as a marketing add-on. It is embedded across demand generation, account-based marketing, sales enablement, and revenue operations—forming a unified growth engine.

    The Future of Lead Generation Is Predictive

    The future of B2B lead generation is not about casting wider nets—it’s about listening better. AI-driven intent data gives organizations the ability to hear buyer signals at scale, interpret them intelligently, and act at precisely the right moment.
    As competition intensifies and buyer journeys become more complex, the companies that win will be those that replace assumptions with intelligence—and volume with precision.

    𝐑𝐞𝐚𝐝 𝐌𝐨𝐫𝐞: https://intentamplify.com/blog/the-future-of-b2b-demand-generation-how-ai-and-intent-data-will-redefine-growth-by-2026/
    How AI-Driven Intent Data Is Transforming B2B Lead Generation in 2026 B2B lead generation is undergoing a fundamental shift. Traditional models built on cold outreach, static buyer personas, and volume-based campaigns are rapidly losing effectiveness. In their place, a smarter, more precise approach is emerging—one powered by artificial intelligence and intent data. By 2026, AI-driven intent intelligence is not just enhancing lead generation; it is redefining how B2B organizations identify, engage, and convert buyers. From Lead Volume to Buying Signals For years, B2B marketing success was measured by the number of leads generated. But high volumes rarely translated into high-quality opportunities. Today’s buyers conduct most of their research independently—reading blogs, comparing vendors, joining webinars, and engaging in online communities long before filling out a form. AI-driven intent data captures these digital footprints and transforms them into actionable buying signals. Rather than guessing who might be interested, organizations can now see which accounts are actively researching specific solutions, which topics they care about, and where they are in the buying journey. This marks a critical shift from lead accumulation to buyer readiness. How AI Makes Intent Data Truly Actionable Intent data alone isn’t new. What’s changed is AI’s ability to analyze massive volumes of behavioral, contextual, and firmographic data in real time. Modern AI engines correlate website activity, content consumption, search behavior, social engagement, and third-party data sources to build dynamic intent profiles. By 2026, these systems can identify patterns humans can’t—predicting purchase likelihood, detecting early-stage research behavior, and continuously refining account prioritization. Instead of static scoring models, B2B teams now operate with living intelligence models that adapt as buyer behavior evolves. This allows sales and marketing teams to focus their efforts on accounts showing genuine buying momentum, dramatically increasing efficiency and conversion rates. Precision Targeting and Hyper-Personalization One of the most powerful impacts of AI-driven intent data is the ability to personalize engagement at scale. When AI understands not only who a buyer is but what problems they are actively trying to solve, messaging becomes instantly more relevant. Marketing teams can automatically tailor campaigns based on real-time interests—serving cybersecurity content to accounts researching breach prevention or ROI-driven messaging to executives evaluating vendors. Sales teams receive insights into pain points, competitive research, and timing signals, enabling outreach that feels helpful rather than intrusive. The result is a shift from disruptive marketing to contextual engagement—meeting buyers exactly where they are. Shorter Sales Cycles, Stronger Pipelines AI-powered intent intelligence also compresses sales cycles. By engaging prospects earlier and with greater relevance, organizations influence decisions before competitors even know a deal exists. Lead qualification becomes predictive rather than reactive, allowing teams to forecast pipeline with greater confidence. In 2026, high-performing B2B organizations no longer treat intent data as a marketing add-on. It is embedded across demand generation, account-based marketing, sales enablement, and revenue operations—forming a unified growth engine. The Future of Lead Generation Is Predictive The future of B2B lead generation is not about casting wider nets—it’s about listening better. AI-driven intent data gives organizations the ability to hear buyer signals at scale, interpret them intelligently, and act at precisely the right moment. As competition intensifies and buyer journeys become more complex, the companies that win will be those that replace assumptions with intelligence—and volume with precision. 𝐑𝐞𝐚𝐝 𝐌𝐨𝐫𝐞: https://intentamplify.com/blog/the-future-of-b2b-demand-generation-how-ai-and-intent-data-will-redefine-growth-by-2026/
    0 Kommentare 0 Geteilt 677 Ansichten
  • Google Willow e il salto quantico: da settilioni di anni a 5 minuti
    Sam Altman assume i coach, Google piega il tempo: le nuove frontiere dell'IA enterprise...

    Il tempo di calcolo necessario per risolvere un problema complesso è appena crollato da dieci settilioni di anni a una manciata di minuti: si tratta di un processo che avrebbe richiesto ai supercomputer più potenti del mondo un'attesa lunga miliardi di volte l'età dell'universo, ma che un nuovo chip di Google ha risolto in meno di cinque minuti. Nei laboratori di Santa Barbara e negli uffici di San Francisco la realtà sta totalmente riscrivendo le gerarchie del potere tecnologico attraverso un doppio binario: da un lato l’assimilazione di competenze umane per rendere l’IA un coach aziendale infallibile, dall’altro il debutto di processori quantistici che sfidano le leggi della fisica classica.

    OpenAI e Convogo: l'intelligenza artificiale impara la leadership
    OpenAI ha aperto il nuovo anno con l'acquisizione del team di Convogo, una mossa che di per se non punta alla tecnologia, piuttosto mira al capitale umano dietro uno strumento nato quasi per scommessa. La genesi di Convogo risiede in un quesito domestico posto dalla madre di uno dei fondatori, una Coach aziendale stanca di dover preparare continuamente dei report: l’obiettivo era automatizzare il lavoro di routine per restituire tempo alla qualità del rapporto umano. Sam Altman ha colto in questa intuizione la chiave per abbattere l’ultimo muro che separa i modelli linguistici dai risultati aziendali tangibili, assumendo esperti di leadership e assessment per trasformare ChatGPT in un consulente capace di dialogare con i vertici delle organizzazioni mondiali.
    Il salto quantico di Google Willow: calcoli impossibili in cinque minuti
    Questa fame di competenze specifiche si scontra con una frontiera tecnologica ancora più estrema, dove è invece Google a primeggiare: recentemente Big G ha mostrato Willow, il chip quantistico racchiuso in una struttura che ricorda un lampadario dorato sospeso nel vuoto. All'interno di questo cilindro, la temperatura viene mantenuta a un millesimo di grado sopra lo zero assoluto, creando l’ambiente più freddo dell’universo conosciuto per permettere ai 105 qubit di operare senza interferenze. Hartmut Neven, a capo della divisione Quantum AI di Google, descrive questa macchina come una chiave universale capace di aprire contemporaneamente mille porte che l’informatica tradizionale deve invece varcare una alla volta.
    Dunque assistiamo a due orizzonti che convergono: l’acquisizione di Convogo da parte di OpenAI suggerisce un’integrazione dell’intelligenza artificiale nel tessuto connettivo della gestione del lavoro, mentre il chip Willow rappresenta il motore che potrebbe rendere tali simulazioni infinitamente più potenti, permettendo di decodificare strutture molecolari o di risolvere crisi climatiche ed energetiche con una velocità precedentemente inimmaginabile.

    La minaccia alla cybersecurity: il rischio «Harvest Now, Decrypt Later»
    La competizione per il dominio di queste tecnologie sembra ricordare una nuova corsa allo spazio, con implicazioni geopolitiche che vanno ben oltre il settore commerciale: gli Stati Uniti procedono attraverso acquisizioni di talenti e laboratori d'avanguardia, la Cina ha centralizzato i propri sforzi in un’impresa statale, investendo circa quindici miliardi di dollari per superare l'Occidente nella comunicazione quantistica.
    Esiste, inoltre, una preoccupazione concreta legata alla sicurezza globale: la capacità di calcolo di macchine come Willow potrebbe, in un futuro non troppo lontano, rendere obsoleti gli attuali sistemi di crittografia, mettendo a rischio segreti di stato (oltre che quelli personali) e l'intera infrastruttura delle criptovalute. Gli esperti parlano già di una strategia definita «raccogli ora, decripta dopo» (harvest now, decrypt later), secondo la quale agenzie governative archiviano dati oggi indecifrabili in attesa che la potenza quantistica permetta di violarli con facilità.
    In questo scenario, infine, muta il confine tra scienza e filosofia, diventa sempre più impalpabile: Neven ha suggerito che l'incredibile velocità di Willow potrebbe essere spiegata con la capacità del chip di attingere a realtà parallele, una suggestione che richiama la formulazione dei molti mondi della meccanica quantistica…ma anche illustri opere di Asimov.

    L’evoluzione dell’intelligenza artificiale sta preparando il terreno per un’era in cui il concetto stesso di risolvibile verrà completamente ridisegnato: l'integrazione di team specializzati nel coaching umano all'interno di colossi tecnologici indica che, nonostante la potenza di calcolo stia per toccare vette quasi mistiche, la capacità di tradurre questi miracoli tecnologici in benefici tangibili per la società rimane la sfida più complessa e, forse, l'unica che non può essere risolta esclusivamente da un processore a temperature sub-zero.

    https://www.avvenire.it/rubriche/artifici/google-willow-e-il-salto-quantico-da-settilioni-di-anni-a-5-minuti_103192
    Google Willow e il salto quantico: da settilioni di anni a 5 minuti Sam Altman assume i coach, Google piega il tempo: le nuove frontiere dell'IA enterprise... Il tempo di calcolo necessario per risolvere un problema complesso è appena crollato da dieci settilioni di anni a una manciata di minuti: si tratta di un processo che avrebbe richiesto ai supercomputer più potenti del mondo un'attesa lunga miliardi di volte l'età dell'universo, ma che un nuovo chip di Google ha risolto in meno di cinque minuti. Nei laboratori di Santa Barbara e negli uffici di San Francisco la realtà sta totalmente riscrivendo le gerarchie del potere tecnologico attraverso un doppio binario: da un lato l’assimilazione di competenze umane per rendere l’IA un coach aziendale infallibile, dall’altro il debutto di processori quantistici che sfidano le leggi della fisica classica. OpenAI e Convogo: l'intelligenza artificiale impara la leadership OpenAI ha aperto il nuovo anno con l'acquisizione del team di Convogo, una mossa che di per se non punta alla tecnologia, piuttosto mira al capitale umano dietro uno strumento nato quasi per scommessa. La genesi di Convogo risiede in un quesito domestico posto dalla madre di uno dei fondatori, una Coach aziendale stanca di dover preparare continuamente dei report: l’obiettivo era automatizzare il lavoro di routine per restituire tempo alla qualità del rapporto umano. Sam Altman ha colto in questa intuizione la chiave per abbattere l’ultimo muro che separa i modelli linguistici dai risultati aziendali tangibili, assumendo esperti di leadership e assessment per trasformare ChatGPT in un consulente capace di dialogare con i vertici delle organizzazioni mondiali. Il salto quantico di Google Willow: calcoli impossibili in cinque minuti Questa fame di competenze specifiche si scontra con una frontiera tecnologica ancora più estrema, dove è invece Google a primeggiare: recentemente Big G ha mostrato Willow, il chip quantistico racchiuso in una struttura che ricorda un lampadario dorato sospeso nel vuoto. All'interno di questo cilindro, la temperatura viene mantenuta a un millesimo di grado sopra lo zero assoluto, creando l’ambiente più freddo dell’universo conosciuto per permettere ai 105 qubit di operare senza interferenze. Hartmut Neven, a capo della divisione Quantum AI di Google, descrive questa macchina come una chiave universale capace di aprire contemporaneamente mille porte che l’informatica tradizionale deve invece varcare una alla volta. Dunque assistiamo a due orizzonti che convergono: l’acquisizione di Convogo da parte di OpenAI suggerisce un’integrazione dell’intelligenza artificiale nel tessuto connettivo della gestione del lavoro, mentre il chip Willow rappresenta il motore che potrebbe rendere tali simulazioni infinitamente più potenti, permettendo di decodificare strutture molecolari o di risolvere crisi climatiche ed energetiche con una velocità precedentemente inimmaginabile. La minaccia alla cybersecurity: il rischio «Harvest Now, Decrypt Later» La competizione per il dominio di queste tecnologie sembra ricordare una nuova corsa allo spazio, con implicazioni geopolitiche che vanno ben oltre il settore commerciale: gli Stati Uniti procedono attraverso acquisizioni di talenti e laboratori d'avanguardia, la Cina ha centralizzato i propri sforzi in un’impresa statale, investendo circa quindici miliardi di dollari per superare l'Occidente nella comunicazione quantistica. Esiste, inoltre, una preoccupazione concreta legata alla sicurezza globale: la capacità di calcolo di macchine come Willow potrebbe, in un futuro non troppo lontano, rendere obsoleti gli attuali sistemi di crittografia, mettendo a rischio segreti di stato (oltre che quelli personali) e l'intera infrastruttura delle criptovalute. Gli esperti parlano già di una strategia definita «raccogli ora, decripta dopo» (harvest now, decrypt later), secondo la quale agenzie governative archiviano dati oggi indecifrabili in attesa che la potenza quantistica permetta di violarli con facilità. In questo scenario, infine, muta il confine tra scienza e filosofia, diventa sempre più impalpabile: Neven ha suggerito che l'incredibile velocità di Willow potrebbe essere spiegata con la capacità del chip di attingere a realtà parallele, una suggestione che richiama la formulazione dei molti mondi della meccanica quantistica…ma anche illustri opere di Asimov. L’evoluzione dell’intelligenza artificiale sta preparando il terreno per un’era in cui il concetto stesso di risolvibile verrà completamente ridisegnato: l'integrazione di team specializzati nel coaching umano all'interno di colossi tecnologici indica che, nonostante la potenza di calcolo stia per toccare vette quasi mistiche, la capacità di tradurre questi miracoli tecnologici in benefici tangibili per la società rimane la sfida più complessa e, forse, l'unica che non può essere risolta esclusivamente da un processore a temperature sub-zero. https://www.avvenire.it/rubriche/artifici/google-willow-e-il-salto-quantico-da-settilioni-di-anni-a-5-minuti_103192
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    Google Willow e il salto quantico: da settilioni di anni a 5 minuti
    Sam Altman assume i coach, Google piega il tempo: le nuove frontiere dell'IA enterprise
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