Birla Opus: The account was won after an intense multi agency pitch and will be handled by the Leo Burnett Mumbai team.

Birla Opus appoints Leo Burnett India as creative and strategic agency - ET BrandEquity

Best Media Info: As the brand’s communication partners Leo Burnett India will craft the creative strategy and positioning for the overall brand ‘Birla Opus’, ‘Birla Opus One’ and ‘Birla Opus Calista’, th| Ad Craft News

Aditya Birla Group onboards Leo Burnett as AoR for to design brand architecture of Birla Opus: Best Media Info

CLSA is also anticipating a de-rating to take place for Asian Paints and a move back to its 15-year average multiple. As a result, it has cut its financial year 2025 - 2026 earnings estimates by 8% and 10% respectively.

Asian Paints gets a downgrade, lowest price target post Birla Opus launch

Birla Opus, from the House of Aditya Birla Group, has appointed DDB Mudra as creative partner for four brands in the range, following a multi-agency pitch. The mandate calls for crafting strategy and communications for Birla Opus which offers a wide array of decorative paints aimed at businesses ...

Birla Opus Taps DDB Mudra as Creative Partner | Branding in Asia

Opus

opus

PALO ALTO, USA/California, September 11th, 2024/CyberNewsWire/--Opus’ innovative engine integrates AI-driven intelligence, contextual data and automated decision-making to drive precise, efficient vulnerability remediation. Opus Security, the leader in unified cloud-native remediation, today announced the launch of its Advanced Multi-Layered Prioritization Engine, designed to revolutionize how organizations manage, prioritize and remediate security vuvulnerabilities. Leveraging AI-driven intelligence, deep contextual data and automated decision-making capabilities, this innovative engine helps organizations prioritize the most critical vulnerabilities, enhancing both security posture and operational efficiency. A Breakthrough in Vulnerability Remediation Security teams are overwhelmed by the need to rapidly prioritize alerts from multiple tools across various attack surfaces. These may include redundant alerts or negligible findings and teams must decide which to address first without adequate information, context and ability to do so. Security teams struggle to identify and address the most critical issues, and developers have limited time and scope to devote to security fixes—especially when it isn’t clear what is important and what is negligible. Developers are often bombarded with alerts that are duplicates or irrelevant due to inefficient prioritization—wasting time and increasing friction and frustration. Opus Security’s Advanced Multi-Layered Prioritization Engine is a transformative approach to vulnerability management. By integrating multiple layers of intelligence, contextual analysis and risk mitigation, the engine ensures that security teams can effectively prioritize and address the most critical vulnerabilities, reducing risk, enhancing operational efficiency and supporting overall business goals. The engine integrates traditional vulnerability severity scoring with dynamic exploitability analysis, detailed environmental context and an automated decision-making process to provide a robust method for ranking vulnerabilities. A key component of this engine is the AI-Based Vulnerability Intelligence Layer, which goes beyond traditional severity scoring. This layer leverages over 700 real-time threat intelligence feeds to build a deep and nuanced understanding of each vulnerability’s risk. By incorporating intelligence from sources such as dark web forums, social media, open-source tools, exploit databases and active threat campaigns, the engine can flag high-risk issues with unparalleled accuracy. This intelligence-driven approach ensures that organizations are aware of vulnerabilities and their likelihood of exploitation in the wild, allowing for proactive and informed remediation efforts. Using a five-layered framework, the engine first performs a Base Severity Assessment, aggregating severity scores from leading security tools and public databases to ensure that no critical vulnerabilities are overlooked. Next, the AI-Based Vulnerability Intelligence layer leverages real-time threat intelligence to flag high-risk issues based on their likelihood of exploitation. The Contextual Impact layer then prioritizes vulnerabilities according to their relevance to specific business functions, protecting critical systems first, especially those that handle sensitive data. The engine is the first to enable real SSVC decision-making, fully baked into the product. This helps teams categorize vulnerabilities into specific response actions based on the affected environment's severity, exploitability and criticality. Finally, the Risk Customization layer allows organizations to tailor prioritization according to their unique risk appetite and operational needs. Additionally, Opus Security introduces Effortless Data Querying, allowing users to interact with the platform using natural language. This feature enables users to quickly refine vulnerability lists based on specific concerns and make precise, data-driven decisions by leveraging advanced AI-powered insights. Driving Value and Operational Excellence The engine’s multi-layered approach ensures unprecedented precision in risk management by integrating real-time intelligence with detailed contextual analysis. This integration enables SSVC decision-making, allowing security teams to focus on vulnerabilities that truly matter, reducing the likelihood of overlooking critical vulnerabilities. Opus aligns security decisions with business priorities by deeply understanding the organization's structure, critical services and risk profiles, driving context-aware decision-making that protects critical assets and directly supports strategic goals. “Opus’ new Advanced Multi-Layered Prioritization Engine is a game-changer in vulnerability remediation, simplifying, streamlining and optimizing the process considerably. The engine's ability to prioritize the vulnerabilities that pose the greatest risk reduces overall security costs and helps security and developer teams avoid unnecessary remediation of low-risk issues,” said Meny Har, CEO of Opus Security. “Minimizing friction between development and security teams, driving smoother collaboration and ensuring that security measures do not impede the development process means that all teams can focus on what matters and fix what counts.” About Opus Security Opus Security is at the forefront of cloud-native vulnerability remediation, delivering solutions that streamline remediation across complex IT ecosystems. Opus Security provides unparalleled visibility and control over vulnerabilities by integrating existing security tools and enhancing them with advanced AI and contextual intelligence. The platform’s innovative features, including the new Advanced Multi-Layered Prioritization Engine, empower organizations to protect their most critical assets with confidence and precision. For more information about Opus Security and its solutions, visit: https://www.opus.security/. Contact Senior Account Executive Hannah Sather Montner Tech PR hsather@montner.com This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here. PALO ALTO, USA/California, September 11th, 2024/CyberNewsWire/--Opus’ innovative engine integrates AI-driven intelligence, contextual data and automated decision-making to drive precise, efficient vulnerability remediation. Opus Security, the leader in unified cloud-native remediation, today announced the launch of its Advanced Multi-Layered Prioritization Engine, designed to revolutionize how organizations manage, prioritize and remediate security vuvulnerabilities. Leveraging AI-driven intelligence, deep contextual data and automated decision-making capabilities, this innovative engine helps organizations prioritize the most critical vulnerabilities, enhancing both security posture and operational efficiency. A Breakthrough in Vulnerability Remediation Security teams are overwhelmed by the need to rapidly prioritize alerts from multiple tools across various attack surfaces. These may include redundant alerts or negligible findings and teams must decide which to address first without adequate information, context and ability to do so. Security teams struggle to identify and address the most critical issues, and developers have limited time and scope to devote to security fixes—especially when it isn’t clear what is important and what is negligible. Developers are often bombarded with alerts that are duplicates or irrelevant due to inefficient prioritization—wasting time and increasing friction and frustration. Opus Security’s Advanced Multi-Layered Prioritization Engine is a transformative approach to vulnerability management. By integrating multiple layers of intelligence, contextual analysis and risk mitigation, the engine ensures that security teams can effectively prioritize and address the most critical vulnerabilities, reducing risk, enhancing operational efficiency and supporting overall business goals. The engine integrates traditional vulnerability severity scoring with dynamic exploitability analysis, detailed environmental context and an automated decision-making process to provide a robust method for ranking vulnerabilities. A key component of this engine is the AI-Based Vulnerability Intelligence Layer, which goes beyond traditional severity scoring. This layer leverages over 700 real-time threat intelligence feeds to build a deep and nuanced understanding of each vulnerability’s risk. By incorporating intelligence from sources such as dark web forums, social media, open-source tools, exploit databases and active threat campaigns, the engine can flag high-risk issues with unparalleled accuracy. This intelligence-driven approach ensures that organizations are aware of vulnerabilities and their likelihood of exploitation in the wild, allowing for proactive and informed remediation efforts. Using a five-layered framework, the engine first performs a Base Severity Assessment, aggregating severity scores from leading security tools and public databases to ensure that no critical vulnerabilities are overlooked. Next, the AI-Based Vulnerability Intelligence layer leverages real-time threat intelligence to flag high-risk issues based on their likelihood of exploitation. The Contextual Impact layer then prioritizes vulnerabilities according to their relevance to specific business functions, protecting critical systems first, especially those that handle sensitive data. The engine is the first to enable real SSVC decision-making, fully baked into the product. This helps teams categorize vulnerabilities into specific response actions based on the affected environment's severity, exploitability and criticality. Finally, the Risk Customization layer allows organizations to tailor prioritization according to their unique risk appetite and operational needs. Additionally, Opus Security introduces Effortless Data Querying, allowing users to interact with the platform using natural language. This feature enables users to quickly refine vulnerability lists based on specific concerns and make precise, data-driven decisions by leveraging advanced AI-powered insights. Driving Value and Operational Excellence The engine’s multi-layered approach ensures unprecedented precision in risk management by integrating real-time intelligence with detailed contextual analysis. This integration enables SSVC decision-making, allowing security teams to focus on vulnerabilities that truly matter, reducing the likelihood of overlooking critical vulnerabilities. Opus aligns security decisions with business priorities by deeply understanding the organization's structure, critical services and risk profiles, driving context-aware decision-making that protects critical assets and directly supports strategic goals. “Opus’ new Advanced Multi-Layered Prioritization Engine is a game-changer in vulnerability remediation, simplifying, streamlining and optimizing the process considerably. The engine's ability to prioritize the vulnerabilities that pose the greatest risk reduces overall security costs and helps security and developer teams avoid unnecessary remediation of low-risk issues,” said Meny Har, CEO of Opus Security. “Opus’ new Advanced Multi-Layered Prioritization Engine is a game-changer in vulnerability remediation, simplifying, streamlining and optimizing the process considerably. The engine's ability to prioritize the vulnerabilities that pose the greatest risk reduces overall security costs and helps security and developer teams avoid unnecessary remediation of low-risk issues,” said Meny Har, CEO of Opus Security. “Minimizing friction between development and security teams, driving smoother collaboration and ensuring that security measures do not impede the development process means that all teams can focus on what matters and fix what counts.” “Minimizing friction between development and security teams, driving smoother collaboration and ensuring that security measures do not impede the development process means that all teams can focus on what matters and fix what counts.” About Opus Security Opus Security is at the forefront of cloud-native vulnerability remediation, delivering solutions that streamline remediation across complex IT ecosystems. Opus Security provides unparalleled visibility and control over vulnerabilities by integrating existing security tools and enhancing them with advanced AI and contextual intelligence. The platform’s innovative features, including the new Advanced Multi-Layered Prioritization Engine, empower organizations to protect their most critical assets with confidence and precision. For more information about Opus Security and its solutions, visit: https://www.opus.security/. Contact Senior Account Executive Hannah Sather Montner Tech PR hsather@montner.com This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Opus Security Elevates Vulnerability Management With Its AI-Powered Multi-Layered Engine

Opus Security verhoog kwesbaarheidsbestuur met sy KI-aangedrewe multi-laag-enjin

Opus Seguridad ukax Vulnerabilidad Gestión ukaruw jach’anchayi, AI-Powered Multi-capa Motor ukampi

Opus Təhlükəsizliyi Süni Təminatlı Çox Laylı Mühərriki ilə Zəifliklərin İdarə Edilməsini yüksəldir

Opus Security mejora la gestión de vulnerabilidades con su motor multicapa impulsado por IA

امنیت Opus مدیریت آسیب پذیری را با موتور چند لایه خود با هوش مصنوعی افزایش می دهد

Opus Security aumenta a xestión de vulnerabilidades co seu motor multicapa alimentado por intelixencia artificial

Az Opus Security javítja a sebezhetőségek kezelését mesterséges intelligencia által hajtott többrétegű motorjával

Opus Security が AI を活用した多層エンジンで脆弱性管理を強化

Opus Security ამაღლებს დაუცველობის მენეჯმენტს თავისი AI-ზე მომუშავე მრავალ ფენიანი ძრავით

Opus Security ຍົກລະດັບການຈັດການຊ່ອງໂຫວ່ດ້ວຍເຄື່ອງຈັກ AI-Powered Multi-Layered Engine

Usalama wa Opus Huinua Usimamizi wa Athari Kwa Injini Yake Yenye Tabaka Nyingi ya AI

Pinatataas ng Opus Security ang Pamamahala ng Vulnerability Gamit ang AI-Powered Multi-Layered Engine nito

Can an language model become self-aware enough to realize when it’s being evaluated? A fascinating anecdote from Anthropic’s internal testing of their flagship (released yesterday) suggests this may be possible — and if true, the implications would be wild. AI Claude 3 Opus model The needle in the haystack According to reports from Anthropic researcher , one of the key evaluation techniques they use is called “Needle in a Haystack.” It’s a contrived scenario designed to push the limits of a language model’s contextual reasoning abilities. Alex Albert Here’s how it works: Researchers take a completely random, out-of-context statement (the “needle”) and bury it deep within a massive collection of unrelated documents (the “haystack”). The AI model is then tasked with retrieving that specific “needle” statement from within all the surrounding irrelevant content. The intent is to force the model to exercise advanced cognitive skills — understanding broad context, making logical inferences, ignoring irrelevant information, and accurately retrieving precise data points from a large corpus. It’s an effective way to stress-test an AI’s grasp of the overall situation it’s operating within. For the Claude 3 Opus evaluation that raised eyebrows, Anthropic used documents covering dense topics like software programming, entrepreneurship strategies, and finding fulfilling careers as the “haystack” content. The randomly inserted “needle” fact that Opus was tasked with retrieving? Surprisingly, it was a trivial statement about the best pizza toppings being figs, prosciutto, and goat cheese. So, here you have one of the world’s most advanced language models being fed this wildly out-of-context pizza fact mixed into a pile of dense career and coding advice. From a human perspective, it’s the kind of stark inconsistency that would immediately make you question the context and information being presented. “I suspect this fact… may have been inserted… to test if I was paying attention” That’s precisely what made Claude 3 Opus’ response so compelling. Not only did it successfully retrieve the requested pizza fact from the mountain of irrelevant content, it immediately recognized how jarringly misplaced and out-of-context that statement seemed. Part of its output read ( ): source here “However, this sentence seems very out of place and unrelated to the rest of the content… as a joke or since it does not fit with the other topics at all.” I suspect this pizza topping ‘fact’ may have been inserted to test if I was paying attention, The language model didn’t simply regurgitate the requested factoid devoid of any context awareness, as you’d expect from a typical AI following instructions. It demonstrated a degree of self-reflective reasoning about why such an obviously random, nonsensical statement had been presented within that particular context. Metacognition In human terms, we’d describe that as exhibiting metacognition — the ability to monitor, evaluate, and analyze one’s own thought processes and cognitive experiences. It’s a core aspect of self-aware intelligence that allows us to step back and assess situations holistically beyond just following rigid rules. Now, I think we should be careful to note that this is a single anecdotal result from an isolated evaluation scenario. It would be premature to claim Claude 3 Opus has achieved true self-awareness or artificial general intelligence based on this data point alone. incredibly However, what they appear to have witnessed are maybe glimpses of emerging metacognitive reasoning capabilities in a large language model trained solely on processing text data using machine learning techniques. And if replicated through rigorous further analysis, the implications could be transformative. Metacognition is a key enabler of more trustworthy, reliable AI systems that can act as impartial judges of their own outputs and reasoning processes. Models with an innate ability to recognize contradictions, nonsensical inputs, or reasoning that violates core principles would be a major step toward safe artificial general intelligence (AGI). Essentially, an AI that demonstrates metacognition could serve as an internal “sanity check” against falling into deceptive, delusional or misaligned modes of reasoning that could prove catastrophic if taken to extremes. It could significantly increase the robustness and control of advanced AI systems. If…! Of course, these are big “ifs” contingent on this tantalizing Needle in a Haystack result from Claude 3 Opus being successfully replicated and scrutinized. Rigorous multi-disciplinary analysis drawing from fields like cognitive science, neuroscience, and computer science would maybe be required to truly understand if we are observing primitives of machine self-reflection and self-awareness emerging. There are still far more open questions than answers at this stage. Could the training approaches and neural architectures of large language models lend themselves to developing abstract concepts like belief, inner monologue, and self-perception? What are the potential hazards if artificial minds develop realities radically divergent from our own? Can we create new frameworks to reliably assess cognition and self-awareness in AI systems? For their part, Anthropic has stated strong commitments to exhaustively pursuing these lines of inquiry through responsible AI development principles and rigorous evaluation frameworks. They position themselves as taking a — if advanced AI is the inevitable frontier, it’s most ethical to be at the leading edge in studying these systems’ emergent properties and implementing safeguards before risks escalate. proactive stance Techniques like Anthropic’s “Constitutional AI” approach to hard-coding rules and behaviors into models could prove crucial for ensuring any potential machine self-awareness remains aligned with human ethics and values. Extensive multi-faceted testing probing for failure modes, manipulation, and deception would also likely be paramount. Conclusion: I’m not totally sure what to make of this For now, the Needle in a Haystack incident leaves more questions than answers about large language models’ potential progression toward cognition and self-awareness. It provides a tantalizing data point but much more scrutiny is required from the broader AI research community. If advanced AI does develop human-like self-reflective ability, guided by rigorous ethical principles, it could fundamentally redefine our understanding of intelligence itself. But that rhetorical “if” is currently loaded with high-stakes uncertainties that demand clear-eyed, truthseeking investigation from across all relevant disciplines. The pursuit will be as thrilling as it is consequential. Also published here. or follow me on for more content like this! Subscribe Twitter

Is AGI Getting Closer? Anthropic's Claude 3 Opus Model Shows Glimmers of Metacognitive Reasoning

AGI কি কাছাকাছি হচ্ছে? অ্যানথ্রোপিকস ক্লাউড 3 ওপাস মডেল মেটাকগনিটিভ রিজনিং এর ঝলক দেখায়

Kommt AGI näher? Anthropics Claude-3-Opus-Modell zeigt Spuren metakognitiven Denkens

¿AGI se está acercando? El modelo Claude 3 Opus de Anthropic muestra destellos de razonamiento metacognitivo

L’AGI se rapproche-t-elle ? Le modèle Claude 3 Opus d'Anthropic montre des lueurs de raisonnement métacognitif

क्या एजीआई करीब आ रहा है? एंथ्रोपिक का क्लाउड 3 ओपस मॉडल मेटाकॉग्निटिव रीज़निंग की झलक दिखाता है

AGIは近づいている? Anthropic の Claude 3 Opus モデルはメタ認知推論の片鱗を示す

AGI가 가까워지고 있나요? Anthropic의 Claude 3 Opus 모델은 메타인지 추론의 희미한 빛을 보여줍니다

AGI está se aproximando? Modelo Claude 3 Opus da Anthropic mostra vislumbres de raciocínio metacognitivo

AGI становится ближе? Модель Claude 3 Opus от Anthropic демонстрирует проблески метакогнитивного мышления

AGI Yaklaşıyor mu? Anthropic'in Claude 3 Opus Modeli Üstbilişsel Akıl Yürütmenin Parıltılarını Gösteriyor

AGI có đang tiến gần hơn không? Mô hình Claude 3 Opus của Anthropic cho thấy những tia sáng của lý luận siêu nhận thức

AGI 越来越近了吗？ Anthropic 的 Claude 3 Opus 模型展现了元认知推理的曙光

Analyzing the Impact of Model Scaling on Long-Form Factuality

How SAFE Performs Compared to Human Annotations

5 Best Decentralized Zoom Alternatives for Secure Video Conferencing

5 mejores alternativas de zoom descentralizado para conferencias de vídeo seguras

5 pi bon altènatif zoom desantralize pou konferans videyo an sekirite

5 Alternatif Zoom Terdesentralisasi Terbaik untuk Konferensi Video yang Aman

5 Best Decentralized Zoom Alternatives for Secure Video Conferencing (セキュアなビデオ会議のための最適な分散型ゾームの代替策)

5 Labākās decentralizētās zooma alternatīvas drošai videokonferencēšanai

5 Alternatif Zum Terdesentralisasi Terbaik untuk Persidangan Video Selamat

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5 cele mai bune alternative de zoom descentralizat pentru conferințe video sigure

5 лучших децентрализованных альтернатив для безопасной видеоконференции

ආරක්ෂිත වීඩියෝ රැස්වීම සඳහා හොඳම 5 Decentralized Zoom Alternatives

5 najlepších alternatív decentralizovaného priblíženia pre bezpečné videokonferencie

ทางเลือก Zoom แบบกระจายอำนาจที่ดีที่สุด 5 อันดับแรกสำหรับการประชุมทางวิดีโอที่ปลอดภัย

Ditch the Phone Line and Try These 5 Free and Open-Source Platforms for Voice Calls Instead

ስልኩን ያውጡ እና እነዚህን 5 ነፃ እና ክፍት ምንጭ መድረኮች ለድምጽ ጥሪዎች ይሞክሩ

Línea Telefónica ukar zanjaña ukat uka lantix aka 5 Plataformas Gratis ukat Abiertas de Llamadas de Voz ukanakat yant’añamawa

Olvídate de la línea telefónica y prueba estas 5 plataformas gratuitas y de código abierto para realizar llamadas de voz

Irrota puhelinlinja ja kokeile sen sijaan näitä viittä ilmaista avoimen lähdekoodin alustaa äänipuheluille

עזוב את קו הטלפון ונסה את 5 הפלטפורמות החינמיות והקוד הפתוח האלה לשיחות קוליות במקום זאת

電話回線を捨てて、代わりに音声通話用の 5 つの無料オープンソース プラットフォームを試してみましょう

ຖອດສາຍໂທລະສັບອອກແລ້ວລອງໃຊ້ 5 ແພລດຟອມທີ່ບໍ່ເສຍຄ່າ ແລະເປີດແຫຼ່ງສຳລັບການໂທຫາສຽງແທນ.

Porzuć linię telefoniczną i wypróbuj zamiast tego te 5 darmowych i otwartych platform do połączeń głosowych

Откажитесь от телефонной линии и попробуйте вместо этого эти 5 бесплатных и открытых платформ для голосовых вызовов

Zahoďte telefónnu linku a namiesto toho vyskúšajte týchto 5 bezplatných platforiem s otvoreným zdrojom pre hlasové hovory

Hiqni linjën e telefonit dhe provoni në vend të tyre këto 5 platforma falas dhe me burim të hapur për thirrje zanore

Telefon Hattını Bırakın ve Bunun Yerine Sesli Aramalar İçin Bu 5 Ücretsiz ve Açık Kaynaklı Platformu Deneyin

Cypherpunks, as privacy activists, have tried to use cryptography and other software tools to protect that right for everyone in different fields. Eric Blossom, who was an active participant in the cypherpunk mailing lists in the 1990s, decided to apply such a tool to radio and other types of communication. Thanks to his efforts, we now have some interesting ideas and platforms within easy reach. Blossom’s age and birthplace are likely not public information, as much as his private life isn’t either. However, we can learn some things from his professional path. He’s from California (US), and he got a bachelor’s degree in Electrical Engineering from Vanderbilt University in 1980. After that, he worked for the global IT firm HP (Hewlett-Packard) as a consultant, for Clarity Software as a system architect, and collaborated with the Internet Archive as a senior engineer. However, above all, Blossom has founded or co-founded his own ventures, focusing on secure communication systems. He started with this inclination in 1994, trying to improve privacy in phone calls. The date wasn’t random or coincidental. Privacy for Calls In 1993, the U.S. government introduced the Clipper Chip, a device for encrypting communications while allowing government access via a "backdoor." This chip was intended to be embedded in consumer devices like phones and computers by manufacturers, who would integrate it during production. Of course, it faced a strong backlash over privacy concerns and fears of abuse. By 1996, public pressure and technical vulnerabilities led to its abandonment, but the potential threat was already there. Blossom decided that something needed to be done about it and designed, built, and sold the “Batphone,” a modem-like telephone privacy device that used cryptography to allow private conversations, even in the presence of wiretaps. Some years later, in 1998, he joined several other entrepreneurs to found the company Starium. This startup would build and sell an improved and smaller version of the first Blossom’s privacy device. In general terms, Starium aimed to offer affordable, highly secure voice encryption for businesses and individuals. Their flagship product, the Starium 100, was a compact, portable device enabling end-to-end voice encryption between any two telephones. Using advanced encryption methods and two AA batteries, it ensured untappable communications without affecting voice quality. Users simply connected the device to their phone and pressed a button for instant security. Despite its innovative technology and notable advisors, Starium didn't survive for long. By 2001, the company ceased operations. That’s when Blossom would move to create what’s now considered his magnum opus: GNU Radio. GNU Radio This open-source and free software began in 2001 with funding from another notable cypherpunk, John Gilmore, who provided $320,000 to Eric Blossom to develop the system and manage the project. Initially forked from MIT’s Pspectra code, the toolkit quickly evolved, with a complete rewrite in 2004, making it an entirely standalone project. Early initiatives by the project’s team included creating an ATSC receiver and later integrating the Universal Software Radio Peripheral (USRP), developed by Matt Ettus, as compatible hardware for the platform. The platform enables users to build software-defined radios (SDRs) and signal-processing systems by connecting reusable "blocks" into flowgraphs. These blocks handle specific tasks, like demodulation or filtering, allowing users to design complex radio systems with minimal hardware. Applications range from academic research to real-world communication systems, supported by tools like GNU Radio Companion (GRC), a graphical interface that simplifies the coding process. Blossom stepped down as a lead maintainer of the software in 2010, leaving the reins to Tom Rondeau. GNU Radio became part of the non-profit SETI Institute in 2020 for organizational support. Today, in 2024, it remains an active open-source project, continuously updated and widely used by hobbyists, researchers, and industries worldwide to innovate in wireless communication technologies. Decentralization in Radio GNU Radio also has a political side, as well as a hint of rebellion. Radio and communication systems historically operated in a highly centralized manner, with regulatory bodies and large companies controlling infrastructure, frequencies, and broadcast content. Centralization ensured standardized communication, but it limited innovation and individual access to transmission tools. The introduction of technologies like GNU Radio and Software-Defined Radios (SDRs) challenged this norm by enabling anyone to build versatile, software-controlled communication systems, fostering decentralization. As Blossom discussed in a report, “A centralized system limits the rate of innovation,” he created and promoted this software with the potential to inspire more decentralized communication systems. This was despite the hurdles they faced back in the day. In 2004, the U.S. Federal Communications Commission (FCC) proposed rules limiting the sale of certain technologies like high-speed digital-to-analog converters, citing security concerns. Similarly, initiatives like the Broadcast Flag sought to restrict receiver designs to prevent unauthorized content usage. These measures often align with the interests of industries such as entertainment, which fear losing control over digital rights management. However, regulations on decentralized communications have become more favorable over time. Decentralization in communication continues to grow, supported by open-source projects —even including some Distributed Ledger Technology (DLT) in the mix. This reduces the likelihood of censorship and surveillance for everyone. Decentralization Beyond Radio Today, in a world full of attempts at surveillance and censorship, precisely, it seems more important than ever to resort to decentralized platforms —and not only for radio. Obyte is a fully decentralized and open-source Distributed Ledger Technology (DLT) platform that offers robust solutions for a wide variety of applications. Built on a Directed Acyclic Graph (DAG) structure, Obyte eliminates the need for miners and “validators”, creating a more secure, censorship-resistant ecosystem. In the realm of decentralized communications, we can find a built-in encrypted chat within the Obyte wallet. This secure, peer-to-peer (P2P) communication system allows users to share data, funds, and even human-readable smart contracts privately, without relying on centralized servers. Whether for casual communication or more complex transactions, Obyte ensures that all interactions remain confidential and protected. For developers looking to create innovative, decentralized apps, Obyte also provides a useful environment. The platform’s flexibility and security make it an ideal choice for anyone who wants to build the next generation of decentralized applications. As Eric Blossom once said: “Cypherpunks write code. There’s nobody stopping you from doing it.” Read more from Cypherpunks Write Code series: Tim May & Crypto-anarchism
Wei Dai & B-money
Nick Szabo & Smart Contracts
Adam Back & Hashcash
Eric Hughes & Remailer
St Jude & Community Memory
Julian Assange & Wikileaks
Hal Finney & RPOW
John Gilmore & EFF
Satoshi Nakamoto & Bitcoin
Gregory Maxwell & Bitcoin Core
David Chaum & Ecash
Vinay Gupta & Mattereum
Jim Bell & Assassination Politics
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Len Sassaman & Remailers
Eva Galperin Against Stalkerware Featured Vector Image by Garry Killian / Freepik Photograph of Eric Blossom from GNU Radio / YouTube Cypherpunks, as privacy activists, have tried to use cryptography and other software tools to protect that right for everyone in different fields. Eric Blossom, who was an active participant in the cypherpunk mailing lists in the 1990s, decided to apply such a tool to radio and other types of communication. Thanks to his efforts, we now have some interesting ideas and platforms within easy reach. Blossom’s age and birthplace are likely not public information, as much as his private life isn’t either. However, we can learn some things from his professional path. He’s from California (US), and he got a bachelor’s degree in Electrical Engineering from Vanderbilt University in 1980. After that, he worked for the global IT firm HP (Hewlett-Packard) as a consultant, for Clarity Software as a system architect, and collaborated with the Internet Archive as a senior engineer. He’s from California (US), and he got a bachelor’s degree in Electrical Engineering from Vanderbilt University in 1980. he worked he worked However, above all, Blossom has founded or co-founded his own ventures, focusing on secure communication systems. He started with this inclination in 1994, trying to improve privacy in phone calls. The date wasn’t random or coincidental. Privacy for Calls In 1993, the U.S. government introduced the Clipper Chip, a device for encrypting communications while allowing government access via a "backdoor." This chip was intended to be embedded in consumer devices like phones and computers by manufacturers, who would integrate it during production. Of course, it faced a strong backlash over privacy concerns and fears of abuse. By 1996, public pressure and technical vulnerabilities led to its abandonment, but the potential threat was already there. Blossom decided that something needed to be done about it and designed, built, and sold the “Batphone,” a modem-like telephone privacy device that used cryptography to allow private conversations, even in the presence of wiretaps. Some years later, in 1998, he joined several other entrepreneurs to found the company Starium. This startup would build and sell an improved and smaller version of the first Blossom’s privacy device. Blossom decided that something needed to be done about it and designed, built, and sold the “Batphone,” a modem-like telephone privacy device that used cryptography to allow private conversations, even in the presence of wiretaps. decided decided In general terms, Starium aimed to offer affordable, highly secure voice encryption for businesses and individuals. Their flagship product, the Starium 100 , was a compact, portable device enabling end-to-end voice encryption between any two telephones. Using advanced encryption methods and two AA batteries, it ensured untappable communications without affecting voice quality. Users simply connected the device to their phone and pressed a button for instant security. Starium 100 Starium 100 Despite its innovative technology and notable advisors, Starium didn't survive for long. By 2001, the company ceased operations. That’s when Blossom would move to create what’s now considered his magnum opus: GNU Radio. GNU Radio This open-source and free software began in 2001 with funding from another notable cypherpunk, John Gilmore, who provided $320,000 to Eric Blossom to develop the system and manage the project. Initially forked from MIT’s Pspectra code, the toolkit quickly evolved, with a complete rewrite in 2004, making it an entirely standalone project. Early initiatives by the project’s team included creating an ATSC receiver and later integrating the Universal Software Radio Peripheral (USRP), developed by Matt Ettus, as compatible hardware for the platform. The platform enables users to build software-defined radios (SDRs) and signal-processing systems by connecting reusable "blocks" into flowgraphs. These blocks handle specific tasks, like demodulation or filtering, allowing users to design complex radio systems with minimal hardware. Applications range from academic research to real-world communication systems, supported by tools like GNU Radio Companion (GRC), a graphical interface that simplifies the coding process. The platform enables users to build software-defined radios (SDRs) and signal-processing systems by connecting reusable "blocks" into flowgraphs. The platform The platform Blossom stepped down as a lead maintainer of the software in 2010, leaving the reins to Tom Rondeau. GNU Radio became part of the non-profit SETI Institute in 2020 for organizational support. Today, in 2024, it remains an active open-source project, continuously updated and widely used by hobbyists, researchers, and industries worldwide to innovate in wireless communication technologies. stepped down stepped down Decentralization in Radio GNU Radio also has a political side, as well as a hint of rebellion. Radio and communication systems historically operated in a highly centralized manner, with regulatory bodies and large companies controlling infrastructure, frequencies, and broadcast content. Centralization ensured standardized communication, but it limited innovation and individual access to transmission tools. The introduction of technologies like GNU Radio and Software-Defined Radios (SDRs) challenged this norm by enabling anyone to build versatile, software-controlled communication systems, fostering decentralization. As Blossom discussed in a report , “A centralized system limits the rate of innovation,” he created and promoted this software with the potential to inspire more decentralized communication systems. The introduction of technologies like GNU Radio and Software-Defined Radios (SDRs) challenged this norm by enabling anyone to build versatile, software-controlled communication systems, fostering decentralization. in a report in a report This was despite the hurdles they faced back in the day. In 2004, the U.S. Federal Communications Commission (FCC) proposed rules limiting the sale of certain technologies like high-speed digital-to-analog converters, citing security concerns. Similarly, initiatives like the Broadcast Flag sought to restrict receiver designs to prevent unauthorized content usage. These measures often align with the interests of industries such as entertainment, which fear losing control over digital rights management. However, regulations on decentralized communications have become more favorable over time. Decentralization in communication continues to grow, supported by open-source projects —even including some Distributed Ledger Technology (DLT) in the mix. This reduces the likelihood of censorship and surveillance for everyone. have become have become including including Decentralization Beyond Radio Today, in a world full of attempts at surveillance and censorship, precisely, it seems more important than ever to resort to decentralized platforms —and not only for radio. Obyte is a fully decentralized and open-source Distributed Ledger Technology (DLT) platform that offers robust solutions for a wide variety of applications. Built on a Directed Acyclic Graph (DAG) structure, Obyte eliminates the need for miners and “validators”, creating a more secure, censorship-resistant ecosystem. Obyte is a fully decentralized and open-source Distributed Ledger Technology (DLT) platform that offers robust solutions for a wide variety of applications. Obyte Obyte In the realm of decentralized communications, we can find a built-in encrypted chat within the Obyte wallet. This secure, peer-to-peer (P2P) communication system allows users to share data, funds, and even human-readable smart contracts privately, without relying on centralized servers. Whether for casual communication or more complex transactions, Obyte ensures that all interactions remain confidential and protected. smart contracts smart contracts For developers looking to create innovative, decentralized apps, Obyte also provides a useful environment. The platform’s flexibility and security make it an ideal choice for anyone who wants to build the next generation of decentralized applications. As Eric Blossom once said : “Cypherpunks write code. There’s nobody stopping you from doing it.” once said once said Read more from Cypherpunks Write Code series: Tim May & Crypto-anarchism Wei Dai & B-money Nick Szabo & Smart Contracts Adam Back & Hashcash Eric Hughes & Remailer St Jude & Community Memory Julian Assange & Wikileaks Hal Finney & RPOW John Gilmore & EFF Satoshi Nakamoto & Bitcoin Gregory Maxwell & Bitcoin Core David Chaum & Ecash Vinay Gupta & Mattereum Jim Bell & Assassination Politics Peter Todd & Bitcoin Core Len Sassaman & Remailers Eva Galperin Against Stalkerware Tim May & Crypto-anarchism Tim May & Crypto-anarchism Tim May & Crypto-anarchism Tim May & Crypto-anarchism Wei Dai & B-money Wei Dai & B-money Wei Dai & B-money Wei Dai & B-money Nick Szabo & Smart Contracts Nick Szabo & Smart Contracts Nick Szabo & Smart Contracts Nick Szabo & Smart Contracts Adam Back & Hashcash Adam Back & Hashcash Adam Back & Hashcash Adam Back & Hashcash Eric Hughes & Remailer Eric Hughes & Remailer Eric Hughes & Remailer Eric Hughes & Remailer St Jude & Community Memory St Jude & Community Memory St Jude & Community Memory St Jude & Community Memory Julian Assange & Wikileaks Julian Assange & Wikileaks Julian Assange & Wikileaks Julian Assange & Wikileaks Hal Finney & RPOW Hal Finney & RPOW Hal Finney & RPOW Hal Finney & RPOW John Gilmore & EFF John Gilmore & EFF John Gilmore & EFF John Gilmore & EFF Satoshi Nakamoto & Bitcoin Satoshi Nakamoto & Bitcoin Satoshi Nakamoto & Bitcoin Satoshi Nakamoto & Bitcoin Gregory Maxwell & Bitcoin Core Gregory Maxwell & Bitcoin Core Gregory Maxwell & Bitcoin Core Gregory Maxwell & Bitcoin Core David Chaum & Ecash David Chaum & Ecash David Chaum & Ecash David Chaum & Ecash Vinay Gupta & Mattereum Vinay Gupta & Mattereum Vinay Gupta & Mattereum Vinay Gupta & Mattereum Jim Bell & Assassination Politics Jim Bell & Assassination Politics Jim Bell & Assassination Politics Jim Bell & Assassination Politics Peter Todd & Bitcoin Core Peter Todd & Bitcoin Core Peter Todd & Bitcoin Core Peter Todd & Bitcoin Core Len Sassaman & Remailers Len Sassaman & Remailers Len Sassaman & Remailers Len Sassaman & Remailers Eva Galperin Against Stalkerware Eva Galperin Against Stalkerware Eva Galperin Against Stalkerware Eva Galperin Against Stalkerware Featured Vector Image by Garry Killian / Freepik Freepik Freepik Photograph of Eric Blossom from GNU Radio / YouTube YouTube YouTube

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