Mark Klein, president and CEO of San Francisco-based investment firm SuRo Capital, shares his thoughts on why the AI startup market is not just frothy, but “dangerously overheated,” in this Crunchbase News Q&#038;A.

مارك كلاين، رئيس ومدير تنفيذي لشركة سو رو كابيتال، وهي شركة استثمارية مقرها سان فرانسيسكو، أعرب عن قلقه بشأن سوق الشركات الناشئة في مجال الذكاء الاصطناعي، واصفًا إياه بأنه 'مفرط في التسخين بشكل خطير'. في مقابلة حديثة مع كرانشبيس نيوز، أوضح كلاين الحالة الحالية للسوق، مشيرًا إلى أن الحماس المحيط بالاستثمارات في الذكاء الاصطناعي قد لا يكون مستدامًا. تعكس آراؤه تزايد القلق بين المستثمرين بشأن الجدوى على المدى الطويل للعديد من الشركات الناشئة في الذكاء الاصطناعي في ظل المنافسة المتزايدة والتقييمات المبالغ فيها.

Mark Klein, presidente y CEO de SuRo Capital, una firma de inversión con sede en San Francisco, ha expresado su preocupación por el mercado de startups de IA, describiéndolo como 'peligrosamente sobrecalentado'. En una reciente entrevista con Crunchbase News, Klein elaboró sobre el estado actual del mercado, sugiriendo que el entusiasmo en torno a las inversiones en IA puede no ser sostenible. Sus comentarios reflejan una creciente inquietud entre los inversores sobre la viabilidad a largo plazo de muchas startups de IA en medio de una competencia creciente y valoraciones infladas.

Mark Klein, président et PDG de SuRo Capital, une société d'investissement basée à San Francisco, a exprimé des inquiétudes concernant le marché des startups en intelligence artificielle, le qualifiant de 'dangereusement surchauffé'. Dans une récente interview avec Crunchbase News, Klein a détaillé l'état actuel du marché, suggérant que l'enthousiasme entourant les investissements en IA pourrait ne pas être durable. Ses réflexions reflètent une appréhension croissante parmi les investisseurs quant à la viabilité à long terme de nombreuses startups en IA face à une concurrence accrue et à des v…

Mark Klein, the president and CEO of SuRo Capital, a San Francisco-based investment firm, expressed concerns regarding the AI startup market, describing it as 'dangerously overheated.' In a recent Q&A with Crunchbase News, Klein elaborated on the current state of the market, suggesting that the enthusiasm surrounding AI investments may not be sustainable. His insights reflect a growing apprehension among investors about the long-term viability of many AI startups amidst increasing competition and inflated valuations.

Why This OpenAI And CoreWeave Investor Thinks The AI Market Is ‘Dangerously Overheated’

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Samsung's QN90F QLED delivers great streaming and gaming performance, making it a strong holiday value.

Why I recommend this Samsung QLED TV over pricier OLED models in 2025 - and don't regret it

<h1>
 
 
 AI Amnesia: Erasing Knowledge Without a Trace
</h1>

Imagine your AI model accidentally learned something it shouldn't have – sensitive customer data, for example. Current methods for deleting this information often require retraining the entire model, an expensive and time-consuming process. What if we could surgically remove that knowledge without starting from scratch?

The key lies in a novel approach: creating artificial "forgetting cues." We're teaching the model to unlearn specific data patterns by exposing it to carefully crafted synthetic examples. These examples are designed to strongly contradict the information we want the model to forget, effectively overwriting the problematic associations in its memory. This works even if you don’t have access to the original data you need to erase.

Think of it like this: you're trying to forget a bad song stuck in your head. Instead of trying to actively suppress it (which rarely works), you blast an even more catchy song. The new song overwrites the old one, effectively erasing it from your mental playlist.

Benefits of Selective Forgetting:

<ul>
<li> Enhanced Data Privacy: Remove sensitive data without compromising the overall model's performance.</li>
<li> Reduced Retraining Costs: Avoid full model retraining, saving significant time and resources.</li>
<li> Improved Model Security: Eliminate vulnerabilities introduced by unintentionally learned patterns.</li>
<li> Adaptable Learning: Enables continuous refinement of AI models based on evolving data landscapes.</li>
<li> Compliance Ready: Supports compliance with data privacy regulations like GDPR.</li>
<li> Scalable Solutions: Works efficiently even with limited access to training data.</li>
</ul>

Practical Tip: One challenge is ensuring the synthetic data accurately targets the information you want to remove without negatively impacting the model's ability to generalize. Rigorous testing and validation with holdout datasets are crucial.

The promise of AI that can truly 'forget' opens exciting possibilities for responsible AI development. By enabling precise data deletion, we pave the way for more secure, compliant, and adaptable machine learning systems. Imagine AI models that can adapt to changing ethical guidelines or quickly unlearn incorrect information, all without massive retraining efforts. This is a crucial step towards trustworthy and responsible AI that respects data privacy and aligns with societal values. Future exploration could include extending this to different data modalities and model architectures.

Related Keywords: machine unlearning, data privacy, few-shot learning, zero-shot learning, synthetic data, model editing, catastrophic forgetting, incremental learning, continual learning, deep learning, neural networks, data security, algorithmic fairness, responsible ai, ethical ai, federated unlearning, privacy-preserving ai, model retraining, AI governance, data deletion, GDPR compliance

يتناول المقال نهجًا جديدًا لمعالجة مشكلة نسيان الذكاء الاصطناعي، حيث قد تحتفظ نماذج الذكاء الاصطناعي عن غير قصد بمعلومات حساسة. تتطلب الطرق التقليدية لحذف هذه البيانات غالبًا إعادة تدريب كاملة للنموذج، وهو ما يعد مكلفًا ويستغرق وقتًا. تتضمن التقنية الجديدة إنشاء 'إشارات نسيان' اصطناعية تساعد النموذج على نسيان أنماط بيانات معينة من خلال تعريضه لأمثلة صناعية تتناقض مع المعلومات غير المرغوب فيها، مما يسمح بإزالة المعرفة المستهدفة دون الحاجة للوصول إلى البيانات الأصلية.

El artículo aborda un nuevo enfoque para tratar el problema de la amnesia de la IA, donde los modelos de IA pueden retener inadvertidamente información sensible. Los métodos tradicionales para eliminar estos datos a menudo requieren un reentrenamiento completo del modelo, lo que es costoso y lleva tiempo. La nueva técnica implica crear 'señales de olvido' artificiales que ayudan al modelo a desaprender patrones de datos específicos al exponerlo a ejemplos sintéticos que contradicen la información no deseada, permitiendo así la eliminación selectiva de conocimientos sin necesidad de acceder a l…

L'article traite d'une nouvelle approche pour résoudre le problème de l'amnésie de l'IA, où les modèles d'IA peuvent involontairement conserver des informations sensibles. Les méthodes traditionnelles pour supprimer ces données nécessitent souvent un réentraînement complet du modèle, ce qui est coûteux et long. La nouvelle technique consiste à créer des 'cues d'oubli' artificiels qui aident le modèle à désapprendre des schémas de données spécifiques en lui présentant des exemples synthétiques qui contredisent les informations indésirables, permettant ainsi une suppression ciblée des connaissan…

The article discusses a novel approach to address the issue of AI amnesia, where AI models may inadvertently retain sensitive information. Traditional methods for deleting such data often require complete retraining of the model, which is costly and time-consuming. The new technique involves creating artificial 'forgetting cues' that help the model unlearn specific data patterns by presenting it with synthetic examples that contradict the unwanted information, allowing for targeted knowledge removal without needing access to the original data.

AI Amnesia: Erasing Knowledge Without a Trace

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Traveling soon? Why this one charger is the only one you'll ever need to pack

Turning materials like wood chips, crop residues and municipal solid waste into fuels and chemicals is important for our country's energy independence.

طور الباحثون نماذج حاسوبية متقدمة تهدف إلى تحسين التنبؤات لعمليات طحن الكتلة الحيوية. تركز هذه الابتكارات على تحويل مواد مثل رقائق الخشب، بقايا المحاصيل، والنفايات الصلبة البلدية إلى وقود ومواد كيميائية قيمة، وهو أمر مهم لتعزيز استقلالية الطاقة في البلاد. من المتوقع أن تعمل النماذج على تحسين كفاءة معالجة الكتلة الحيوية، مما يساهم في حلول الطاقة المستدامة.

Investigadores han desarrollado modelos informáticos avanzados destinados a mejorar las predicciones para los procesos de molienda de biomasa. Esta innovación se centra en convertir materiales como astillas de madera, residuos de cultivos y residuos sólidos municipales en combustibles y productos químicos valiosos, lo que es crucial para mejorar la independencia energética del país. Se espera que los modelos optimicen la eficiencia del procesamiento de biomasa, contribuyendo así a soluciones energéticas sostenibles.

Des chercheurs ont développé des modèles informatiques avancés visant à améliorer les prévisions pour les processus de broyage de la biomasse. Cette innovation se concentre sur la conversion de matériaux tels que les copeaux de bois, les résidus de culture et les déchets solides municipaux en combustibles et produits chimiques précieux, ce qui est crucial pour renforcer l'indépendance énergétique du pays. Les modèles devraient optimiser l'efficacité du traitement de la biomasse, contribuant ainsi à des solutions énergétiques durables.

Researchers have developed advanced computer models aimed at improving predictions for biomass milling processes. This innovation focuses on converting materials such as wood chips, crop residues, and municipal solid waste into valuable fuels and chemicals, which is crucial for enhancing energy independence in the country. The models are expected to optimize the efficiency of biomass processing, thereby contributing to sustainable energy solutions.

Researchers develop computer models for better biomass milling predictions

The most interesting aspect of the latest Even Realities glasses may be their limitations.

I've tried several AI smart glasses (including Meta Ray-Bans) in 2025 - these are the most comfortable

<a href="https://writer.com/">Writer</a>, a San Francisco-based artificial intelligence startup, is launching a unified AI agent platform designed to let any employee automate complex business workflows without writing code — a capability the company says distinguishes it from consumer-oriented tools like <a href="https://copilot.microsoft.com/">Microsoft Copilot</a> and <a href="https://chatgpt.com/">ChatGPT</a>.The platform, called <a href="https://writer.com/agents/">Writer Agent</a>, combines chat-based assistance with autonomous task execution in a single interface. Starting Tuesday, enterprise customers can use natural language to instruct the AI to create presentations, analyze financial data, generate marketing campaigns, or coordinate across multiple business systems like Salesforce, Slack, and Google Workspace—then save those workflows as reusable &quot;Playbooks&quot; that run automatically on schedules.The announcement comes as enterprises struggle to move AI initiatives beyond pilot programs into production at scale. Writer CEO May Habib has been outspoken about this challenge, recently revealing that 42% of Fortune 500 executives surveyed by her company said AI is &quot;<a href="https://venturebeat.com/ai/ai-is-tearing-companies-apart-writer-ai-ceo-slams-fortune-500-leaders-for">tearing their company apart</a>&quot; due to coordination failures between departments.&quot;We&#x27;re delivering an agent interface that is both incredibly powerful and radically simple to transform individual productivity into organizational impact,&quot; Habib said in a statement. &quot;Writer Agent is the difference between a single sales rep asking a chatbot to write an outreach email and an enterprise ensuring that 1,000 reps are all sending on-brand, compliant, and contextually-aware messages to target accounts.&quot;<h2>How Writer is putting workflow automation in the hands of non-technical workers</h2>The platform&#x27;s core innovation centers on making workflow automation accessible to non-technical employees—what Writer executives call &quot;democratizing who gets to be a builder.&quot;In an exclusive interview with VentureBeat, Doris Jwo, Writer&#x27;s director of product management, demonstrated how the system works: A user types a request in plain English — for example, &quot;Create a two-page partnership proposal between [Company A] and [Company B], make it a branded deck, include impact metrics and partnership tiers.&quot;The AI agent then breaks down that request into discrete steps, conducts web research, generates graphics and charts on the fly, creates individual slides with sourced information, and assembles a complete presentation. The entire process, which might take an employee hours or days, can be completed in 10-12 minutes.&quot;The agent basically looks at the request, breaks it down, does research, understands what pieces it needs, creates a detailed plan at a step-by-step level,&quot; Jwo explained during a product demonstration. &quot;It might say, &#x27;I need to do web research,&#x27; or &#x27;This user needs information from Gong or Slack,&#x27; and it reaches out to those connectors, grabs the data, and executes the plan.&quot;Crucially, users can save these multi-step processes as Playbooks—reusable templates that colleagues can deploy with a single click. Routines allow those Playbooks to run automatically at scheduled intervals, essentially putting knowledge work &quot;on autopilot.&quot;<h2>Security and compliance controls: Writer&#x27;s answer to enterprise IT concerns</h2>Writer positions these enterprise-focused controls as a key differentiator from competitors. While <a href="https://microsoft.com/">Microsoft</a>, <a href="https://openai.com/">OpenAI</a>, and <a href="https://www.anthropic.com/">Anthropic</a> offer powerful AI capabilities, Writer&#x27;s executives argue those tools weren&#x27;t designed from the ground up for the security, compliance, and governance requirements of large regulated organizations.&quot;All of the products you mentioned are great products, but even Copilot is very much focused on personal productivity—summarizing email, for example, which is important, but that&#x27;s not the component we&#x27;re focusing on,&quot; said Matan-Paul Shetrit, Writer&#x27;s director of product management, in an exclusive interview with VentureBeat.Shetrit emphasized Writer&#x27;s &quot;trust, security, and interoperability&quot; approach. IT administrators can granularly control what the AI can access — for instance, preventing market research agents from mentioning competitors, or restricting which employees can use web search capabilities. All activity is logged with detailed audit trails showing exactly what data the agent touched and what actions it took.&quot;These fine-grained controls are what make products enterprise-ready,&quot; Shetrit said. &quot;We can deploy to tens of thousands or hundreds of thousands of employees while maintaining the security and guardrails you need for that scale.&quot;This architecture reflects <a href="https://writer.com/company/about/">Writer&#x27;s origin story</a>. Unlike OpenAI or Anthropic, which started as research labs and later added enterprise offerings, Writer has targeted Fortune 500 companies since its 2020 founding. &quot;We&#x27;re not a research lab that went to consumer and is dabbling in enterprise,&quot; Shetrit said. &quot;We are first and foremost targeting the Global 2000 and Fortune 500, and our research is in service of these customers&#x27; needs.&quot;<h2>Inside Writer&#x27;s strategy to connect AI agents across enterprise software systems</h2>A critical technical component is Writer&#x27;s approach to system integrations. The platform includes pre-built connectors to more than a dozen enterprise applications—<a href="https://workspace.google.com/lp/business/?utm_source=google&amp;utm_medium=cpc&amp;utm_campaign=1710046-Workspace-DR-NA-US-en-Google-BKWS-EXA-na&amp;utm_content=c-Hybrid+%7C+BKWS+-+EXA+%7C+Txt-Google+Workspace-Core-346911454270&amp;utm_term=google%20workspace&amp;gclsrc=aw.ds&amp;gad_source=1&amp;gad_campaignid=20159848966&amp;gclid=CjwKCAiAz_DIBhBJEiwAVH2XwDbhidrT22spa5fU8uNyySir49xeTOAji42tQEy7zvzTZpUAL4TFgRoCLz8QAvD_BwE">Google Workspace</a>, <a href="https://www.microsoft.com/en-us/microsoft-365">Microsoft 365</a>, <a href="https://www.snowflake.com/en/">Snowflake</a>, <a href="https://asana.com/">Asana</a>, <a href="https://slack.com/">Slack</a>, <a href="https://www.gong.io/">Gong</a>, <a href="https://www.hubspot.com">HubSpot</a>, <a href="https://www.atlassian.com/">Atlassian</a>, <a href="https://www.databricks.com/">Databricks</a>, <a href="https://pitchbook.com/">PitchBook</a>, and <a href="https://www.factset.com/">FactSet</a>—allowing the AI to retrieve information and take actions across those systems.Writer built these connectors using the <a href="https://www.anthropic.com/news/model-context-protocol">Model Context Protocol (MCP)</a>, an emerging standard for AI system integrations, but added what Shetrit described as an &quot;enterprise-ready&quot; layer on top.&quot;We took a first-principle approach of: You have this MCP connector infrastructure—how do you build it in a way that&#x27;s enterprise-ready?&quot; Shetrit explained. &quot;What we have today in the industry is definitely not it.&quot;The system can write and execute code on the fly to handle unexpected scenarios. If a user uploads an unfamiliar file format, for instance, the agent will generate code to extract and process the text without requiring a human to intervene.Jwo demonstrated this capability with a daily workflow she runs: Every morning at 10 a.m., a Routine automatically summarizes her Google Calendar meetings, identifies external participants, finds their LinkedIn profiles, and sends the summary to her via Slack — all without her involvement.&quot;This was pretty simple, but you can imagine for a salesperson it might say, &#x27;At the end of the day, wrap up a summary of all the calls I had, send me action items, post it to the account-specific Slack channel, and tag these folks so they can accomplish those workflows,&#x27;&quot; Jwo said. &quot;That can run continuously each day, each week, or on demand.&quot;<h2>From mortgage lenders to CPG brands: Real-world AI agent use cases across industries</h2>The platform is attracting customers across multiple industries. <a href="https://www.newamericanfunding.com/">New American Funding</a>, a mortgage lender, uses Writer Agent to automate marketing workflows. Senior Content Marketing Manager Karen Rodriguez uploads Asana project tickets with creative briefs, and the AI executes tasks like updating email campaigns or transforming articles into social media carousels, video scripts, and captions.Other use cases span financial services teams creating investment dashboards with <a href="https://pitchbook.com/">PitchBook</a> and <a href="https://www.factset.com/">FactSet</a> data, consumer packaged goods companies brainstorming new product lines based on social media trends, and marketing teams generating partnership presentations with branded assets.Writer has added customers including <a href="https://www.tiktok.com/en/">TikTok</a>, <a href="https://www.cmcsa.com/">Comcast</a>, <a href="https://www.keurigdrpepper.com/">Keurig Dr Pepper</a>, <a href="https://www.caa.com/">CAA</a>, and <a href="https://www.aptitudehealth.com/">Aptitude Health</a>, joining an existing base that includes <a href="https://www.accenture.com/">Accenture</a>, <a href="https://www.qualcomm.com/">Qualcomm</a>, <a href="https://www.uber.com/">Uber</a>, <a href="https://investor.vanguard.com/corporate-portal">Vanguard</a>, and <a href="https://www.marriott.com/default.mi">Marriott</a>. The company now serves more than 300 enterprises and has secured over $50 million in signed contracts, with projections to double that to $100 million this year.The startup&#x27;s net retention rate — a measure of how much existing customers expand their usage — stands at 160%, meaning customers on average increase their spending by 60% after initial contracts. Twenty customers who started with $200,000-$300,000 contracts now spend about $1 million annually, according to company data.<h2>&#x27;Vibe working&#x27;: Writer&#x27;s vision for AI-powered productivity beyond coding</h2>Writer executives frame the platform as enabling what they call &quot;vibe working&quot; — a playful reference to the popular term &quot;vibe coding,&quot; which describes AI tools like Cursor that dramatically accelerate software development.&quot;We used to call it transformation when we took 12 steps and made them nine. That&#x27;s optimizing the world as it is,&quot; Habib said at Writer&#x27;s AI Leaders Forum earlier this month, according to <a href="https://www.forbes.com/sites/stevenwolfepereira/2025/11/08/what-writers-ai-leaders-forum-revealed-about-enterprise-ai/">Forbes</a>. &quot;We can now create a new world. That is the greenfield mindset.&quot;Shetrit echoed this framing: &quot;Vibe coding is the theme of 2025. Our view is that ‘vibe working’ is the theme of 2026. How do you bring the same productivity gains you&#x27;ve seen with coding agents into the workspace in a way that non-technical users can maximize them?&quot;The platform is powered by <a href="https://writer.com/engineering/long-context-palmyra-x5/">Palmyra X5</a>, Writer&#x27;s proprietary large language model featuring a one-million-token context window — among the largest commercially available. Writer trained the model for approximately $700,000, a fraction of the estimated $100 million OpenAI spent on GPT-4, by using synthetic data and techniques that halt training when returns diminish.The model can process one million tokens in about 22 seconds and costs 60 cents per million input tokens and $6 per million output tokens — significantly cheaper than comparable offerings, according to company specifications.<h2>Making AI Decisions Visible: Writer&#x27;s Approach to Trust and Transparency</h2>A distinctive aspect of Writer&#x27;s approach is transparency into the AI&#x27;s decision-making process. The interface displays the agent&#x27;s step-by-step reasoning, showing which data sources it accessed, what code it generated, and how it arrived at outputs.&quot;There&#x27;s a very clear exhibition of how the agent is thinking, what it&#x27;s doing, what it&#x27;s touching,&quot; Shetrit said. &quot;This is important for the end user to trust it, but also important for the IT person or security professional to see what&#x27;s going on.&quot;This &quot;supervision&quot; model goes beyond simple observability of API calls to encompass what Shetrit described as &quot;a superset of observability&quot; — giving organizations the ability to not just monitor but control AI behavior through policies and permissions.Session logs capture all agent activity when enabled by administrators, and users can submit feedback on every output to help improve system performance. The platform also emphasizes providing sources and citations for generated content, allowing users to verify information.&quot;With any sort of chat assistant, agentic or not, trust but verify is really important,&quot; Jwo said. &quot;That&#x27;s part of the pillars of us building this and making it enterprise-grade.&quot;<h2>What Writer Agent Costs—and Why It&#x27;s Included in the Base Platform</h2>Writer is including all the new capabilities—Playbooks, Routines, Connectors, and Personality customization—as part of its core platform without additional charges, according to Jwo.&quot;This is fully included as part of the Writer platform,&quot; she said. &quot;We&#x27;re not charging additional for using Writer Agent.&quot;The &quot;Personality&quot; feature allows individual users, teams, or entire organizations to customize the AI&#x27;s communication style, ensuring generated content matches brand voice and tone guidelines. This works alongside company-level controls that enforce terminology and style requirements.For highly structured, repetitive tasks, Writer also offers a library of more than 100 pre-built agents and an AI Studio for building custom multi-agent systems aligned with specific business use cases.<h2>The Race to Define Enterprise AI: Can Purpose-Built Platforms Beat Tech Giants?</h2>The launch crystallizes a fundamental tension in how enterprises will adopt AI at scale. While consumer-facing AI tools emphasize individual productivity gains, companies need systems that work reliably across thousands of employees, integrate with existing software infrastructure, maintain regulatory compliance, and deliver measurable business impact.Writer&#x27;s wager is that these requirements demand purpose-built enterprise platforms rather than consumer tools adapted for business use. The company&#x27;s <a href="https://techcrunch.com/2024/11/12/generative-ai-startup-writer-raises-200m-at-a-1-9b-valuation/">$1.9 billion valuation</a> — achieved in a November 2024 funding round that raised $200 million — suggests investors see merit in this thesis. Backers include <a href="https://www.premjiinvest.com/">Premji Invest</a>, <a href="https://radical.vc/">Radical Ventures</a>, <a href="https://www.iconiqcapital.com/growth">ICONIQ Growth</a>, <a href="https://salesforceventures.com/">Salesforce Ventures</a>, and <a href="https://www.adobe.com/ventures.html">Adobe Ventures</a>.Yet the competitive landscape remains formidable. Microsoft and Google command enormous distribution advantages through their existing enterprise software relationships. OpenAI and Anthropic possess research capabilities that have produced breakthrough models. Whether Writer can maintain its differentiation as these giants expand their enterprise offerings will test the startup&#x27;s core premise: that serving Fortune 500 companies from day one creates advantages that research labs turned enterprise vendors cannot easily replicate.&quot;We&#x27;re entering an era where if you can describe a better way to work, you can build it,&quot; Jwo said. &quot;The new Writer Agent democratizes who gets to be a builder, empowering the operational experts and creative problem-solvers in every department to become the architects of their own transformation. That&#x27;s how you unlock innovation that competitors can&#x27;t replicate.&quot;The promise is alluring — AI capabilities powerful enough to transform how work gets done, accessible enough for any employee to use, and controlled enough for enterprises to deploy safely at scale. Whether Writer can deliver on that promise at the speed and scale required will determine if its vision of &quot;vibe working&quot; becomes the 2026 theme Shetrit predicts, or just another ambitious attempt to solve enterprise AI&#x27;s execution problem.But one thing is certain: In a market where 85% of AI initiatives fail to escape pilot purgatory, Writer is betting that the winners won&#x27;t be the companies with the most powerful models—they&#x27;ll be the ones that make those models actually work inside the enterprise.

تقوم شركة Writer، وهي شركة ناشئة في مجال الذكاء الاصطناعي مقرها في سان فرانسيسكو، بإطلاق منصة موحدة لوكلاء الذكاء الاصطناعي تهدف إلى تمكين الموظفين من أتمتة سير العمل التجاري المعقد دون الحاجة إلى كتابة كود. تُسمى المنصة Writer Agent، وتجمع بين المساعدة القائمة على الدردشة وتنفيذ المهام بشكل مستقل. اعتبارًا من يوم الثلاثاء، يمكن للعملاء من الشركات استخدام اللغة الطبيعية لتوجيه الذكاء الاصطناعي لإنشاء العروض التقديمية وتحليل البيانات المالية، وحفظ هذه العمليات كـ 'Playbooks' قابلة لإعادة الاستخدام تعمل تلقائيًا.

Writer, una startup de inteligencia artificial con sede en San Francisco, está lanzando una plataforma unificada de agentes de IA que permite a los empleados automatizar flujos de trabajo comerciales complejos sin necesidad de programar. La plataforma, llamada Writer Agent, combina asistencia basada en chat con ejecución autónoma de tareas. A partir del martes, los clientes empresariales pueden usar lenguaje natural para instruir a la IA en tareas como crear presentaciones y analizar datos financieros, guardando estos flujos de trabajo como 'Playbooks' reutilizables que se ejecutan automáticam…

Writer, une startup d'IA basée à San Francisco, lance une plateforme d'agents IA unifiée permettant aux employés d'automatiser des flux de travail commerciaux complexes sans coder. La plateforme, nommée Writer Agent, intègre une assistance par chat avec une exécution autonome des tâches. À partir de mardi, les clients d'entreprise peuvent utiliser un langage naturel pour demander à l'IA de créer des présentations et d'analyser des données financières, en sauvegardant ces flux de travail sous forme de 'Playbooks' réutilisables qui s'exécutent automatiquement.

Writer, a San Francisco-based AI startup, is launching a unified AI agent platform that allows employees to automate complex business workflows without coding. The platform, named Writer Agent, integrates chat-based assistance with autonomous task execution. Starting Tuesday, enterprise customers can use natural language to instruct the AI for tasks such as creating presentations and analyzing financial data, saving these workflows as reusable 'Playbooks' that run automatically.

Writer's AI agents can actually do your work—not just chat about it

A Reddit user posted video of his safety driver sleeping at the wheel in San Fransisco.

نشر مستخدم على موقع ريديت مقطع فيديو يظهر فيه سائق أمان لخدمة الروبوتات التابعة لشركة تسلا نائمًا أثناء القيادة في سان فرانسيسكو. يثير هذا الحادث مخاوف بشأن تدابير السلامة المتبعة في عمليات المركبات الذاتية القيادة، خاصة مع دفع شركات مثل تسلا نحو اعتماد أوسع لتكنولوجيا القيادة الذاتية. وقد أثار الفيديو نقاشات على وسائل التواصل الاجتماعي حول موثوقية هذه الأنظمة ومسؤوليات سائقي الأمان.

Un video publicado por un usuario de Reddit muestra a un conductor de seguridad del servicio de robotaxi de Tesla durmiendo al volante en San Francisco. Este incidente plantea preocupaciones sobre las medidas de seguridad implementadas para las operaciones de vehículos autónomos, especialmente a medida que empresas como Tesla impulsan una adopción más amplia de la tecnología de conducción autónoma. El video ha generado discusiones en las redes sociales sobre la fiabilidad de estos sistemas y las responsabilidades de los conductores de seguridad.

Une vidéo publiée par un utilisateur de Reddit montre un conducteur de sécurité du service robotaxi de Tesla endormi au volant à San Francisco. Cet incident soulève des préoccupations concernant les mesures de sécurité mises en place pour les opérations de véhicules autonomes, surtout alors que des entreprises comme Tesla poussent pour une adoption plus large de la technologie de conduite autonome. La vidéo a suscité des discussions sur les réseaux sociaux concernant la fiabilité de ces systèmes et les responsabilités des conducteurs de sécurité.

A video posted by a Reddit user shows a safety driver for Tesla's robotaxi service sleeping while driving in San Francisco. The incident raises concerns about the safety measures in place for autonomous vehicle operations, especially as companies like Tesla push for wider adoption of self-driving technology. The video has sparked discussions on social media regarding the reliability of such systems and the responsibilities of safety drivers.

Tesla safety driver falls asleep during passenger’s robotaxi ride

This is not a large-scale public launch, nor a commercial one. But it brings the Amazon-owned company one step closer to competing with Waymo.

تستعد شركة زوكس، المملوكة لأمازون، لبدء تقديم خدمات سيارات الأجرة الروبوتية للجمهور في سان فرانسيسكو. هذه المبادرة ليست إطلاقًا عامًا على نطاق واسع ولا خدمة تجارية، لكنها تمثل خطوة مهمة لشركة زوكس في سعيها للتنافس مع الشركات الرائدة في سوق سيارات الأجرة الذاتية القيادة، وخاصة وايمو. يسلط هذا التحرك الضوء على الاهتمام المتزايد والاستثمار في حلول النقل الذاتية.

Zoox, la empresa de vehículos autónomos propiedad de Amazon, comenzará a ofrecer viajes en robotaxi al público en San Francisco. Esta iniciativa no es un lanzamiento público a gran escala ni un servicio comercial, pero representa un paso significativo para Zoox en su objetivo de competir con jugadores establecidos en el mercado de taxis autónomos, especialmente Waymo. Este movimiento destaca el creciente interés y la inversión en soluciones de transporte autónomo.

Zoox, la société de véhicules autonomes appartenant à Amazon, va commencer à proposer des trajets en robotaxi au public à San Francisco. Cette initiative ne constitue pas un lancement public à grande échelle ni un service commercial, mais elle représente une étape significative pour Zoox qui vise à rivaliser avec des acteurs établis sur le marché des taxis autonomes, notamment Waymo. Ce mouvement souligne l'intérêt croissant et l'investissement dans les solutions de transport autonome.

Zoox, the autonomous vehicle company owned by Amazon, is set to begin offering robotaxi rides to the public in San Francisco. This initiative is not a large-scale public launch or a commercial service, but it represents a significant step for Zoox as it aims to compete with established players in the autonomous taxi market, particularly Waymo. The move highlights the growing interest and investment in autonomous transportation solutions.

Zoox to begin offering robotaxi rides to public in San Francisco

In an agentic era, the scarcest resource has become the judgment of executives who know how to orchestrate AI systems effectively, writes guest author Pukar C. Hamal of SecurityPal. In this commentary, he shares the asymmetric approach that helps founders compete with VCs for the people needed to advance their startup.

In An Agentic Era, VC Is Buying A-Player C-Suite Execs At Any Cost — Not ‘Staffing Up’

Expense management company Ramp has raised yet another round of capital — its fourth in 2025 alone — this time a $300 million venture round at a $32 billion valuation, the company announced on Monday.

Why This OpenAI And CoreWeave Investor Thinks The AI Market Is ‘Dangerously Overheated’

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