Torsten Boettjer

🌟 Less than a month until CloudSummit in Wiesbaden, May 14-16! Dive into the latest advancements in cloud computing with sessions on #CloudSecurity, #MachineLearning, #ServerlessComputing, and #Compliance strategies. Whether you're refining your skills or exploring new technologies, we have something for everyone. Don’t miss out—check our full agenda and make your plans! https://lnkd.in/eMBztAWn #CloudSummit #CloudTech

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Exciting News! 🌟  Our CEO, Patrik Heider, recently sat down with Philipp Haas from investresearch for an in-depth interview! 🎙️ In this insightful conversation, Patrik delves into our company’s journey and next steps. 🚀 Catch the full conversation here: https://lnkd.in/duqu33d3 #Leadership #Transformation #InvestResearch #CEOInterview #SustainableProfitableGrowth #BusinessGrowth #PatrikHeider

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Last week, our colleagues Vivien Pfeiffer and Ferenc Domröse hosted a webinar with Thomas Köppner from Apptio, an IBM Company, on "FinOps: Unit Costs for Smarter Decisions". Missed it? Here's a snapshot of essential insights into unit costs in FinOps. Reach out to us today, and let's elevate your FinOps strategy together! #UnitCosts #FinOps #CloudCostManagement

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🚀 𝑨 𝒈𝒖𝒊𝒅𝒆 𝒇𝒐𝒓 𝒃𝒖𝒊𝒍𝒅𝒊𝒏𝒈 𝒔𝒆𝒄𝒖𝒓𝒆 𝑰𝒏𝒕𝒆𝒓𝒏𝒂𝒍 𝑫𝒆𝒗𝒆𝒍𝒐𝒑𝒆𝒓 𝑷𝒍𝒂𝒕𝒇𝒐𝒓𝒎𝒔 𝒊𝒏 𝒓𝒆𝒈𝒖𝒍𝒂𝒕𝒆𝒅 𝒆𝒏𝒗𝒊𝒓𝒐𝒏𝒎𝒆𝒏𝒕𝒔 🚀 At PlatformCON 24, André Alfter from Bechtle, explains how they help customers in highly regulated environments build Internal Developer Platforms (IDPs). He explains why platform engineering is a good option for organizations that need very secure IT solutions and how this approach improves security. 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬: 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬: - Customers face challenges in deploying cloud-native, containerized applications across multiple environments. - The biggest challenge is often organizational resistance to change rather than technical issues. - Many customers focus too much on infrastructure provisioning rather than specifying workloads or orchestrating platforms. - Automation tools holding critical configuration data pose a risk when accessible by external developers. 𝐎𝐯𝐞𝐫𝐜𝐨𝐦𝐢𝐧𝐠 𝐭𝐡𝐞 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬: - Collaboration: Encourage engineering teams and developers to work closely together. - Reference Architecture: Utilize a reference architecture that aligns with existing technologies and infrastructure. - Abstraction: Use friendly abstractions to separate the concerns of engineers and developers, allowing each to use tools suited to their roles. - Open-source project Score helps developers define their application's requirements while engineers manage resource provisioning. - Standardize technology stacks to simplify maintenance and operation. - A standardized approach and proper documentation can significantly speed up developer onboarding and productivity. - Experiment with new technologies through guided steps to quickly bring developers and engineers into production. - Collect feedback promptly to iterate and improve processes and platform capabilities. #internaldevelopmentplatform #platformengineering #platformengineers

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When it comes to AI, I might be a bit of a "black sheep". I consider myself a skeptical realist. What I mean by that is: 1. I think AI certainly has the potential to increase output capacity. 2. I think AI will most certainly redefine the labor market in the coming 30-40 years. 3. I think companies that intelligently and strategically adopt AI will have an advantage over those who don't. 4. I think we're still in the early adopter stage of the adoption curve, which means there's certainly still a place to gain a competitive advantage. 5. I think many small and mid-sized companies probably underestimate the cost of deploying/applying AI into their businesses. 6. I think AI probably poses a risk in terms of potentiating the market position of large firms over small firms and potentially will lead to problems of market consolidation. I've included an article from Forbes here that outlines what the costs of building foundational models looks like, which is why most companies that are trying to take on any kind of AI initiative are building off of foundational models and not pursuing the creation of their own. And in so doing, they are working more towards prompt-engineering to iterate on internal PoCs and will then end up having to move towards more defined approaches to going from PoC to production (NOT A SMALL TASK....wink wink). And in this, a lot of organizations might have to rethink their data architecture as it pertains to data availability, data integrity, and cloud costs to even attempt to really deploy AI models across the organization. There are more complex questions to be had, as well, regarding federated data models within multi-national organizations as well as the overall backend software architecture of their tools and systems. At the end of the day, AI isn't just a buzzword. Yes, it represents a before and after, as did the internet. But taking advantage of it requires an holistic, strategic approach to leveraging it within the organization. (Let's not even get into organizational culture and risk aversion based on executive team personalities) With this said, a lot of capitalizing on AI comes down to getting back to basics and executing very well. If you're talking with companies who are treating AI like a magic bullet, they probably aren't the companies that are actually going to lead you to success. If you're looking for a reliable technology partner with a seasoned track record of helping companies navigate complex, cross-functional digital transformation initiatives - from innovating digital channels to migrating to microservices or transitioning data architectures to cloud-based data lakehouses, feel free to connect and we'd be happy to explore whether and how Coderio Software Company can help you not just execute but excel. Oh - and here's that Forbes article: https://lnkd.in/dWb6tAHE

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A new agreement between operator Telefonica and Google Cloud is designed to ‘accelerate Telefonica’s cloud adoption and AI-powered innovation.’ Read more from Telecoms.com on this story here: https://lnkd.in/eP7kQ8Da #TelcoInnovation #AI #GenAI #Cloud #Google #DataAnalytics #CloudMigration #Telecoms #InformaTech #InformaTechTelcoInnovation

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After leaving OpenAI, Leopold Aschenbrenner (part of the super-alignment team that mitigates AI risks) published a “situational awareness” document claiming that only a few 100 AI insiders (mostly in SF AI labs) are aware of how AI will reshape the years ahead. Interesting weekend read (loooong 165 pages) https://lnkd.in/g_i59FDn What blew my mind is how AI asssited AI research will compress how quickly AI will progress! Like the premise from movie Matrix “the first ultra intelligent machine is the last invention that man need ever make” what do you think of his reasoning and predictions?

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Not all digital transformations are fully integrated into existing processes. Often, gaps remain where old methods and new technologies don't quite align. What strategies do you employ to ensure that #digitaltransformation is fully integrated into your business processes? #DigitalTransformation #ProcessIntegration #TechAdoption #ContinuousImprovement #InnovationBlend

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Residuals have always been a complex part of the entertainment business—and then streaming upped the ante. For our client, a U.S. media giant, we created a cloud-native custom residuals application to replace its decades-old legacy system. The new application runs smoothly on AWS and lets the studio scale and manage the end-to-end business flow with a customized rules engine. We also migrated an astonishing 31 years of data to the new app. The result is a streamlined residuals process that handles digital-era payment volumes and contracts—and positions the studio to manage the future of content distribution. https://bit.ly/4crEflu #streaming #entertainment #mediaandentertainment #Cognizant

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By OpenAI CAN private companies pushing forward the frontier of a revolutionary new technology be expected to operate in the interests of both their shareholders and the wider world? When we were recruited to the board of OpenAl -Tasha in 2018 and Helen in 2021 - we were cautiously optimistic that the company's innovative approach to self-governance could offer a blueprint for responsible artificial intelligence (Al) development. But based on our experience, we believe that self-governance cannot reliably withstand the pressure of profit incentives. With Al's enormous potential for both positive and negative impact, it's not sufficient to assume that such incentives will always be aligned with the public good. For the rise of Al to benefit everyone, governments must begin building effective regulatory frameworks now.

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Microsoft just released an open source model (Phi-3) that, on standard benchmarks, beats GPT 3.5, but Phi-3 is half the size of GP-3. This is a big deal. Why does this matter? smaller models are cheaper to run, more efficient, and in this case, can run on edge devices (e.g., phones). This model reinforces the notion that the quality of the data is critical in training LLMs. And importantly, it moves the bar even higher- we can start expecting smaller, more efficient LLMS (or SMLS- Small Language Models), from multiple players. Whether these smaller models, once customized for specific applications can perform better than large ones remains to be seen, but I think that's likely to be the case. #Microsoft #AI #LLMs #SMLS #ArtificialIntelligence

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Leopold Aschenbrenner’s “Situational Awareness: The Decade Ahead" is an exceptionally compelling piece. He argues that the United States must tackle artificial intelligence (AI) with the urgency reminiscent of the Manhattan Project. Aschenbrenner, a leading figure in the AI community, envisions a future where Artificial General Intelligence (AGI) could emerge as early as 2027, with superintelligent systems shortly thereafter. His 165-page essay meticulously details the path from current AI technologies to AGI and beyond, underscoring the strategic imperative for the U.S. to secure its AI research and infrastructure. Drawing a parallel to the nuclear arms race, Aschenbrenner emphasizes the critical need for America to maintain its leadership in AI development. He calls for robust collaboration between AI labs and national defense, proposing the establishment of an AGI-industrial complex to ensure AI advancements bolster American security interests. #ai #superintelligence #sovereignai

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Love this meme demonstrating the challenges to deploy GenAI. That’s why we focus on use cases & outcomes first via Dell OEM Engineering Solutions with our AI & GenAI ecosystem partners. What problem are you trying to solve Mr customer? What is the data strategy to support the outcome? Small agile steps to prove business progress & outcomes is key to build out long term sustainable GenAI adoption. Yes mistake is part of the journey but it’s a lot less painful for a small stumble than the giant spectacular fall that your business might never recover from. #genai Dell Technologies OEM Solutions #iwork4dell

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What i missed in just several days or so in multi-model GenAI innovation… In their own words: 1. ElevenLabs Generate lifelike speech in any language and voice with the most powerful text to speech (TTS) technology that combines advanced AI with emotive capabilities. Indistinguishable from Human Speech. Ideal for digital creators, get high-quality TTS streaming instantly. Let your content go beyond text with our realistic AI voices. Generate high-quality spoken audio in any voice, style, and language. Our AI voice generator is powered by an AI model that renders human intonation and inflections with unrivaled fidelity, adjusting the delivery based on context. 2. Hedra Introducing Character-1: Generate video with expressive and controllable human characters. * Infinite duration (30s for open preview) * 90s generated per 60s (if our H100 supply holds) * Expressive talking, singing, rapping characters This is the first step in Hedra’s mission to build a multimodal creation studio accessible for everyone, giving creators complete control over emotional dialogue, movement, and (yes) entire worlds. 3. Google DeepMind Video-to-audio research uses video pixels and text prompts to generate rich soundtracks. Our V2A technology is pairable with video generation models like Veo to create shots with a dramatic score, realistic sound effects or dialogue that matches the characters and tone of a video 4. Runway Gen-3 Alpha is the first of an upcoming series of models trained by Runway on a new infrastructure built for large-scale multimodal training. It is a major improvement in fidelity, consistency, and motion over Gen-2, and a step towards building General World Models. Trained jointly on videos and images, Gen-3 Alpha will power Runway's Text to Video, Image to Video and Text to Image tools, existing control modes such as Motion Brush, Advanced Camera Controls, Director Mode as well as upcoming tools for more fine-grained control over structure, style, and motion. 5. OpenAI and Color Health Color Health uses the reasoning capabilities of GPT-4o to help doctors transform cancer care. Color Health(opens in a new window) is working with OpenAI to pioneer a new way of accelerating cancer patients’ access to treatment. Their new copilot application uses GPT-4o to identify missing diagnostics and create tailored workup plans, enabling healthcare providers to make evidence-based decisions about cancer screening and treatment. Oh and Nvidia market capitalization is > 3 trillion #genAI #video #reality #perception

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🚨 Do you know how to create real-time #deepfakes? 🚨 One of the techniques used is #FaceSwapping! In 2021 and 2022, my colleagues Samuel Ménard, Liyun He Guelton, and Johan Maes worked on identifying machine learning-based solutions to create and detect these kinds of deepfakes. Fast forward to today, the techniques and solutions for Face Swapping have evolved significantly and are easily accessible! I recently created this video that showcases the ease of creating #deepfakes. What surprised me the most was being able to achieve this in real-time on my current PC (with a simple Nvidia graphics card), there were still some delays between the audio and visual synchronization. Even if tools are available for extracting facial images from videos, manually defining face outlines, and creating Digital Face Manipulation (DFM) models, creating high-quality #FaceSwapping models may require a significant time investment: just for a single face, you must let the GPU work for at least several days, or weeks! What do you think about this video? Can you spot a deepfake? Leave me a comment! Acknowledging the advancements in anti-spoofing solutions is crucial to maintaining #Trust in #Digital. As technologies continue to progress rapidly, it's vital to stay ahead and identify innovative solutions against deepfakes. #Worldline #GenAI #DeepfakeTechnology #RealTimeDeepfakes #MachineLearning #DigitalSecurity.

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▶️The acquisition of VMware by Broadcom has prompted a profound shift on the modern IT landscape. In this changing market, let’s explore different solutions to VMware and the journey from legacy systems to cloud-native solutions. Join our webinar with Portworx by Pure Storage “From Legacy to Cloud Native” on May 16 and learn how you can build a platform on your existing hardware in a cloud native way. Secure your spot 👉 https://hubs.li/Q02sJnWj0 #Kubernetes #k8s #cloudnative #opensource #vmwarealternative #cloudmigration #virtualization #VMwareExit

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ZDNet Innovation Index Highlights - AI Transforming Industries AI dominates the rankings, underscoring its transformative potential in medicine and education. 1. Heidelberg University Hospital - AI-Enhanced Oncology Support Researchers at Germany's Heidelberg University Hospital take the top spot by integrating generative AI models with an external information database. This use of retrieval-augmented generation (RAG) significantly enhances the AI's ability to provide accurate oncology-related answers. The innovation promises to reduce the administrative burden on doctors, allowing them to focus more on patient care amidst a global oncologist shortage. 2. OpenAI's ChatGPT Edu - Revolutionizing Education OpenAI's education-focused ChatGPT secures second place. With customized pricing, this initiative aims to make the enterprise-level chatbot accessible to students and educators. By partnering early with educational institutions, OpenAI is set to influence the future of AI in education, facilitating technology adoption in a sector traditionally slow to change. 3. 3D-Printed Homes - Addressing Housing Inequality In third place, the concept of 3D-printed homes offers a novel solution to housing inequality. This technology could cut construction costs and provide a scalable method to address one of humanity's most pressing issues. While there are challenges to overcome, the potential benefits make it a promising innovation. 4. Amazon's Project P.I. - Enhancing Customer Service Amazon's Project P.I. rounds out the list by using AI to detect product defects and verify order details before shipment. This initiative aims to reduce packaging waste and transport emissions, aligning with climate-forward goals, while significantly improving customer service. These innovations highlight AI's growing influence across diverse sectors, promising significant improvements in efficiency, accessibility, and sustainability. #Innovation #AIinMedicine #AIinEducation #3DPrinting #SustainableTech https://lnkd.in/g6DeBZuZ

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AI STRATAGEMS - Charting the Course of AI, One Strategic Insight at a Time CapEx spending by major cloud providers has surged after the introduction of GPT-3, with AWS, Azure, and Google Cloud each investing over $12B in Q1/24 and trending up. That's approximately the cost of a Gerald R. Ford-class nuclear-powered aircraft carrier.

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