Google and Adobe tumbled last week on OpenAI competitive threats.

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Highlight is an in-home product testing platform that lets you do good research fast. We streamline everything from recruit to data set, including all the logistics of getting your product to your target customers, whether they are cat-owning millennials or women over 50 in California with oily skin looking for retinol.

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At Highlight, we face a unique challenge when it comes to adapting to a load of our customers. Because we record our customers' web apps, we need to be able to handle bursts of traffic as they come from their users. When we first started, our data ingested was simple: we would stream data from our recording client to our backend and perform updates as it came in. Our data handlers would perform metadata updates and write session recordings to PostgreSQL via SQL queries, and they would be consumed and removed from the database tables for permanent storage. The initial approach worked fine for a while. But as our customer base grew, we ran into key issues with this implementation. We had to run some database migrations that ran an ALTER command with an aggressive table lock. Immediately, we saw a wave of blocked commands, all waiting for the migration to complete. For the ~30 minutes that this took, we were dead in the water with incoming session requests and could not store any of our customers' recordings. All of the backend traffic would time out since we didn't have a place to put the data in the meantime. Maintaining all of our customers' recordings is always our top priority, so we knew we had to find a way to improve our ingest. Possible Solutions Since we needed a way to buffer data, we considered various techniques that could accomplish the task. One idea was to abstract each backend payload into a 'message' to be put into a buffer and consumed by a worker. We had a few considerations that were driven by details about our data: Our task data can range from ~10KB to ~100MB Tasks must be processed in order and serially for a given recording. Tasks across different recordings can be processed in parallel. We can't lose any messages for a recording as that would invalidate the entire recording. / / / Other NoSQL Databases Apache Cassandra MongoDB DynamoDB Has row size limits that vary but generally do not support our ~100MB messages. Would require much more application-level logic to write and consume data. Redis Data may expire, so messages may be lost. Message ordering is harder to maintain without performance constraints. RabbitMQ Fully ordered so scalability without application-level re-architecture may be a challenge. Brokers are replicated but do not scale well horizontally. Apache Kafka Messages can be as large as ~500MB. Messages are ordered within a partition. One consumer per partition allows for consistent ordering with linear parallel scaling. Messages only expire after a time-based or space-based retention policy. Building a Scalable Task Queue As we evaluated our options, we settled on a producer-consumer message strategy. Our architecture would have our backend HTTP request handlers produce 'task' messages that would block until the data was sent to our chosen broker. The messages would arrive at the broker quickly and reside until a worker machine could consume them and process their data. This effectively decouples our incoming data stream from the processing, allowing us to buffer data for as long as we want (space permitting based on the configuration of our broker). Focusing on the specifics of Apache Kafka, we had to define partitions that would store the sets of messages. As part of the process, we needed to think of a key that would ensure decide which messages fall into the same partition and are ordered relative to each other. Since one of our requirements is ensuring that tasks for a given recording are processed serially, we chose the session ID as the partition key. On both the producing and consuming ends, we could arbitrarily scale up the number of concurrent processes. Since messages of the same recording are processed in order, consumer scaling is limited. This is based on the number of partitions since, to maintain this property, each partition only has one consumer. For example, to be able to scale up to 128 consumers, we would need to have at least 128 partitions. Note that increasing the number of partitions increases overhead on the Kafka broker nodes and will require a more powerful machine (primarily more memory). For reference, we easily consume/produce ~5k messages per second (each ~100KB on average) across 768 partitions on a 3-node AWS kafka.m5.2xlarge cluster. Our 5 Key Learnings on Apache Kafka Managing our Apache Kafka cluster has been fairly straightforward, but we learned a lot of lessons along the way. To manage the cluster, we set server-side configuration via AWS MSK and monitor/edit topics via an ECS container running . Certain actions normally require the use of the running within the cluster's VPC, but we've found this UI to accomplish most of those tasks well. provectuslabs/kafka-ui Kafka CLI Message Ordering Producers must send messages with the Kafka SDK configuration of acks=all to guarantee message ordering. means that each producer will send the message to ALL brokers and wait for them to all receive the message before continuing. Messages are delivered to all replicas of a particular partition in the same sequence, ensuring that consumers of that partition observe the data in identical order. This setting Log Compaction As we learned the hard way, enabling log compaction for a message broker. Log compaction will replace old messages of a given key with future messages of the same key. This may be useful if messages represent a state which is updated by a superset state, but this approach will cause data loss if each message represents a unique piece of data. is a bad idea Replication Factor / Minimum In-Sync Replica One important feature of Apache Kafka is the ability to replicate data across multiple brokers to ensure high availability. Each partition can be replicated across N brokers to allow for reliable read/writes when a broker is down for maintenance or due to issues. For example, if you have a Kafka cluster with three nodes and a replication factor of three, then all brokers will have copies of all the data. You could lose a node without worrying about data loss and with minimal impact on read/write performance. The replication factor can be configured for the entire server or per data topic. You can find more information about how to configure that here. The setting dictates how many brokers must acknowledge a message before it is considered sent out. You may want to increase this setting to ensure that data is replicated and ordered correctly in the case of a broker outage. However, take care not to set the value to the total number of brokers since that would mean that writing will be blocked if even a single broker is offline for maintenance. min.insync.replicas Data Compression When thinking about how to best compress data, you have two options: compress on the producer/consumer nodes or have the Kafka brokers do it for you. We went with the first option of compressing before sending data and decompressing upon retrieval to ease the load on our cluster. Scaling up our producers/consumers proved to be more cost-effective than adding more CPU/brokers to the Kafka cluster. To accomplish this, we used the client library which provides an excellent abstraction for interacting with the cluster and will handle data compression completely transparently. segmentio/kafka-go Rebalance Timeout As we discussed, a consumer group distributed partitions to all processes so that each partition has exactly one consumer. To accomplish this, consumers send heartbeats to the broker to ensure they are still able to receive messages. When a consumer process stops, such as when rolling out an upgrade or if a worker ECS container crashes, Kafka must detect the missed heartbeat and assign the partition to a new consumer so that its messages do not back up. Two key settings dictate the configuration of rebalancing. By default, the setting governs the duration without consumer heartbeats that a broker considers the consumer dead and initiates a rebalance, and the setting sets the amount of time that the group coordinator will wait for new members to join. This means that once a consumer process stops, the amount of time until new data is consumed is the sum of the two settings. session.timeout.ms group.initial.rebalance.delay.ms We had to tweak these two settings from their default values to ensure that the rebalance time is reasonably short to quickly resume consuming messages while giving enough of a delay for new containers and processes to start up and connect to the cluster. Originally published here.

Is Kafka the Key? The Evolution of Highlight's Ingest

How to Implement Multi-Group Bar Chart and Interact With Highlighting by Grouping Dimension

The 2024 NAB Show featured a lot about, expectedly, AI and the journey within the media and entertainment sectors. Qvest, a leader in digital transformation across broadcast, media, and entertainment, shared new insights into how Fortune 1000 major studios and network players are navigating the complex yet promising terrain of Artificial Intelligence (AI). This exploration into AI adoption strategies reveals a calculated yet visionary approach towards harnessing AI to redefine content creation, management, and distribution. The Emergence of AI Councils and Task Forces A notable trend from Qvest's comprehensive analysis points to a strategic pivot within the industry: about 80% of these media juggernauts have initiated AI Councils or Task Forces. This move signifies a nuanced blend of anticipation and prudence, as these entities explore AI's capabilities through the lens of proofs of concept, focusing on areas like enterprise copilots, service area enhancements, localization, and content optimization. These steps mark the industry's commitment to remaining at the vanguard of technological innovation, albeit with a keen eye on budgetary constraints. The Introduction of the GenAI Maturity Model Among the insights shared at NAB 2024, Qvest's GenAI Maturity Model stands out, offering a structured path for organizations to leverage AI effectively. This model delineates a journey from AI awareness and experimentation to full operational integration and optimization, encapsulating the essence of strategic AI adoption for sustained innovation and competitive edge. The transition towards AI integration is not without its challenges. The findings highlight a critical balance between enhancing operational efficiency and preserving creative autonomy—a dynamic that underscores the need for a comprehensive governance framework and a culture that embraces technological advancements. Early Engagement with AI Technologies Qvest's insights from NAB 2024 underscore a clear call-to-action for the media and entertainment industry: the time to engage with AI is now. Early adoption and strategic integration of AI technologies are crucial to ensuring competitiveness and success in a rapidly evolving digital landscape. This proactive stance is essential for navigating the future of media, where efficiency, innovation, and agility are the benchmarks of industry leadershipThe necessity for media companies to embrace AI technologies has never been more critical. Digital transformation is unforgiving to hesitance; technology will advance faster than companies can keep up with if they remain on the sidelines. Continuous improvement emerges as the real milestone in this journey. Christophe Ponsart, EVP & GenAI Practice Co-Lead, Qvest US, shared this call to action to organizations, “Just dive in and begin. Delaying further minimizes opportunities for growth and potential returns. If there's an area that aligns with potential use cases, use it as a starting point to glean insights and embark on a journey of continuous improvement, which is at the heart of the GenAI process. The goal is to achieve ongoing enhancement in GenAI capabilities, leveraging these insights to build a stronger foundation for future advancements." This advice underscores the essential truth that inaction is the greater risk, urging companies to take proactive steps now or risk being left behind as technology forges ahead without them. Qvest's presence at the event underscores the practical impact and advantages of Generative AI across the media sector. Highlighting the potential of GenAI, Qvest introduces solutions that revolutionize Customer Relationship Management (CRM) processes, enhance ad sales strategies with a language model-based Copilot, refine content licensing operations, and automate the creation of marketing materials. A notable example of Qvest's innovation is TV Buddy, a Conversational AI service designed to boost viewer engagement through interactive communication. The company shared its collaborative solution and automation platform, qibb. As an Integration Platform as a Service (iPaaS), qibb is engineered to facilitate automated, scalable workflows throughout the entire media supply chain. It utilizes a low-code engine to meet the industry’s growing demand for streamlined, secure, and adaptable operations at an optimal cost. Key features include: Simplification of media workflow automation and process inefficiencies via an accessible low-code engine, complemented by customizable dashboards.
Agility in testing, integrating, and swapping GenAI products with ease, supported by generic connectors for a wide range of applications.
Comprehensive and effortless integration of AI tools, provided by a rich catalog that includes over 100 applications, with more than 20 specifically focusing on AI.
Minimized reliance on third-party vendors and reduced operational costs, thus fast-tracking the learning process internally and enhancing operational agility. As the industry reflects on the insights from NAB Show 2024, Qvest's analysis provides a valuable roadmap for media companies. The journey towards AI-driven transformation is complex, yet undeniably promising. For Fortune 1000 major studios and network players, the path forward involves a strategic, informed approach to AI adoption—one that promises to revolutionize the media and entertainment landscape for years to come. ** The 2024 NAB Show featured a lot about, expectedly, AI and the journey within the media and entertainment sectors. Qvest , a leader in digital transformation across broadcast, media, and entertainment, shared new insights into how Fortune 1000 major studios and network players are navigating the complex yet promising terrain of Artificial Intelligence (AI). This exploration into AI adoption strategies reveals a calculated yet visionary approach towards harnessing AI to redefine content creation, management, and distribution. Qvest The Emergence of AI Councils and Task Forces The Emergence of AI Councils and Task Forces A notable trend from Qvest's comprehensive analysis points to a strategic pivot within the industry: about 80% of these media juggernauts have initiated AI Councils or Task Forces. A notable trend from Qvest's comprehensive analysis points to a strategic pivot within the industry: about 80% of these media juggernauts have initiated AI Councils or Task Forces. A notable trend from Qvest's comprehensive analysis points to a strategic pivot within the industry: about 80% of these media juggernauts have initiated AI Councils or Task Forces. This move signifies a nuanced blend of anticipation and prudence, as these entities explore AI's capabilities through the lens of proofs of concept, focusing on areas like enterprise copilots, service area enhancements, localization, and content optimization. These steps mark the industry's commitment to remaining at the vanguard of technological innovation, albeit with a keen eye on budgetary constraints. The Introduction of the GenAI Maturity Model The Introduction of the GenAI Maturity Model Among the insights shared at NAB 2024, Qvest's GenAI Maturity Model stands out, offering a structured path for organizations to leverage AI effectively. This model delineates a journey from AI awareness and experimentation to full operational integration and optimization, encapsulating the essence of strategic AI adoption for sustained innovation and competitive edge. The transition towards AI integration is not without its challenges. The findings highlight a critical balance between enhancing operational efficiency and preserving creative autonomy—a dynamic that underscores the need for a comprehensive governance framework and a culture that embraces technological advancements. Early Engagement with AI Technologies Early Engagement with AI Technologies Qvest's insights from NAB 2024 underscore a clear call-to-action for the media and entertainment industry: the time to engage with AI is now. Early adoption and strategic integration of AI technologies are crucial to ensuring competitiveness and success in a rapidly evolving digital landscape. This proactive stance is essential for navigating the future of media, where efficiency, innovation, and agility are the benchmarks of industry leadershipThe necessity for media companies to embrace AI technologies has never been more critical. Digital transformation is unforgiving to hesitance; technology will advance faster than companies can keep up with if they remain on the sidelines. Continuous improvement emerges as the real milestone in this journey. Christophe Ponsart, EVP & GenAI Practice Co-Lead, Qvest US, shared this call to action to organizations, “Just dive in and begin. Delaying further minimizes opportunities for growth and potential returns. If there's an area that aligns with potential use cases, use it as a starting point to glean insights and embark on a journey of continuous improvement, which is at the heart of the GenAI process. The goal is to achieve ongoing enhancement in GenAI capabilities, leveraging these insights to build a stronger foundation for future advancements." This advice underscores the essential truth that inaction is the greater risk, urging companies to take proactive steps now or risk being left behind as technology forges ahead without them. Qvest's presence at the event underscores the practical impact and advantages of Generative AI across the media sector. Highlighting the potential of GenAI, Qvest introduces solutions that revolutionize Customer Relationship Management (CRM) processes, enhance ad sales strategies with a language model-based Copilot, refine content licensing operations, and automate the creation of marketing materials. A notable example of Qvest's innovation is TV Buddy , a Conversational AI service designed to boost viewer engagement through interactive communication. TV Buddy TV Buddy The company shared its collaborative solution and automation platform, qibb . As an Integration Platform as a Service (iPaaS), qibb is engineered to facilitate automated, scalable workflows throughout the entire media supply chain. It utilizes a low-code engine to meet the industry’s growing demand for streamlined, secure, and adaptable operations at an optimal cost. qibb qibb Key features include: Simplification of media workflow automation and process inefficiencies via an accessible low-code engine, complemented by customizable dashboards. Agility in testing, integrating, and swapping GenAI products with ease, supported by generic connectors for a wide range of applications. Comprehensive and effortless integration of AI tools, provided by a rich catalog that includes over 100 applications, with more than 20 specifically focusing on AI. Minimized reliance on third-party vendors and reduced operational costs, thus fast-tracking the learning process internally and enhancing operational agility. Simplification of media workflow automation and process inefficiencies via an accessible low-code engine, complemented by customizable dashboards. Agility in testing, integrating, and swapping GenAI products with ease, supported by generic connectors for a wide range of applications. Comprehensive and effortless integration of AI tools, provided by a rich catalog that includes over 100 applications, with more than 20 specifically focusing on AI. Minimized reliance on third-party vendors and reduced operational costs, thus fast-tracking the learning process internally and enhancing operational agility. As the industry reflects on the insights from NAB Show 2024, Qvest's analysis provides a valuable roadmap for media companies. The journey towards AI-driven transformation is complex, yet undeniably promising. For Fortune 1000 major studios and network players, the path forward involves a strategic, informed approach to AI adoption—one that promises to revolutionize the media and entertainment landscape for years to come. **

Qvest Shares Key AI Findings at NAB Show 2024, Highlighting Major Trends in Media and Entertainment

Regardless of the industry they operate in or the number of people they employ, businesses with mature observability practices can respond to incidents faster — and save time and money in the process, according to the second annual . Grafana Labs Observability Survey Organizations are making observability a critical part of their software development lifecycles as they grapple with the complexity of modern applications. However, this year’s survey makes it clear that not everyone is at the same stage of adoption, with teams that are further behind struggling to keep up with the always-on demands of today’s users. More than 300 observability practitioners participated in the survey. They shared their thoughts on a wide range of topics, including the varying degrees of maturity, the sheer volume of tools in use, the lingering concerns about expenses, and the ubiquity of open-source tools in this still-emerging market. Key Takeaways From the Grafana Labs Observability Survey You can to learn what respondents had to say about these topics and more, but for a quick assessment of the state of observability, here are the five key takeaways from the survey. read the full survey Observability Practices Are Still Maturing We gauged where respondents were in their journeys by asking how they approached observability.  A little over half say their organization has taken a proactive approach, which points to the growth in this space. However, organizations are still more likely to be reactive than systematic, which means they often hear about problems from their customers rather than have systems in place to address issues before their users ever find out. (Check out our for more on these designations.) Observability Journey Maturity Model And the different approaches can result in very different outcomes, with . 65% of those with a systematic approach having saved time or money through centralized observability, compared to just 35% of those who take a reactive approach Tool and Data Sprawl Remains a Major Hurdle More than two-thirds of teams use at least four observability technologies, with . In addition, half of Grafana users say they have at least six different data sources configured and actively in use in Grafana. respondents collectively citing more than 60 technologies currently in use This can translate to considerable complexity and overhead, and the bigger the company, the more tools and data sources they have. It’s no wonder that among teams that have centralized observability, 79% say it has saved them time or money as a result. Open Source Is the De Facto Standard We cater to a vibrant open-source community at Grafana Labs. And while that likely skews the results in our survey, there’s no denying the impact of OSS. Eight of the 10 most popular technologies cited in our survey are open source, while an . overwhelming majority of respondents are investing in Prometheus (89%) or OpenTelemetry (85%) Interestingly, there’s considerable overlap between the and communities. Almost 40% of respondents use both in their operations, and more than 50% increased their usage of each project over the past year. Prometheus OpenTelemetry AI Could Play a Big Role — Eventually AI is getting tons of attention these days, but its role in observability is largely aspirational today. Still, observability practitioners remain excited about its potential to accelerate incident response and simplify observability adoption. respondents say they would like to see, with more than three-quarters calling it out. Other top wish-list items for AI include predictive analytics and dashboard generation. Anomaly detection is the most cited AI-enabled feature Cost Emerges as a Top Concern , while other related topics — cardinality, unpredictable bills, and vendor lock-in — are also cited. More than half of respondents say cost is their biggest concern about observability

Navigating the Observability Landscape: Highlights From Grafana Labs’ 2024 Survey

পর্যবেক্ষণযোগ্য ল্যান্ডস্কেপ নেভিগেট করা: গ্রাফানা ল্যাবসের 2024 সমীক্ষা থেকে হাইলাইট

Navigieren in der Observability-Landschaft: Highlights aus der Umfrage 2024 von Grafana Labs

Navegando por el panorama de la observabilidad: aspectos destacados de la encuesta de 2024 de Grafana Labs

Naviguer dans le paysage de l'observabilité : points saillants de l'enquête 2024 de Grafana Labs

ऑब्जर्वेबिलिटी लैंडस्केप को नेविगेट करना: ग्राफाना लैब्स के 2024 सर्वेक्षण की मुख्य विशेषताएं

可観測性の展望をナビゲートする: Grafana Labs の 2024 年調査のハイライト

관측 가능성 환경 탐색: Grafana Labs의 2024년 설문조사 하이라이트

Navegando no cenário de observabilidade: destaques da pesquisa de 2024 do Grafana Labs

Навигация по ландшафту наблюдаемости: основные моменты исследования Grafana Labs за 2024 год

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探索可观测性领域：Grafana Labs 2024 年调查要点

When faced with tough economic conditions, often look to reduce overheads to remain afloat. Given the high inflation and rising interest rates that played out globally in 2023, growth and expansion plans may have been put on hold. But despite the recent downturn, predictions for the year ahead are cautiously optimistic. A recent report from the (IMF) predicts that global economic growth is likely to remain at a steady 3.3% in 2024. business leaders International Monetary Fund Investing in brand and design is one of the most effective ways to remain resilient during an economic downturn, helping companies to stand out from the competition and win the trust of consumers. The most successful brand and are driven by highly skilled professionals with the skills and expertise to execute multifaceted strategies that resonate with audiences. design campaigns Here we present 15 examples of excellence in the field of brand and marketing that are helping companies to thrive in 2024. Hewlett Packard Enterprise Hewlett Packard Enterprise (HPE) stands as a global leader in edge-to-cloud solutions, helping to revolutionize businesses worldwide. With a mission to facilitate seamless connectivity, robust protection, insightful analysis, and decisive action on data and applications from edge to cloud, HPE empowers enterprises to translate insights into tangible actions with unparalleled agility in today’s dynamic landscape. , serves as the Brand Strategy Manager for Hewlett Packard Enterprise. In his position at the helm of brand strategy, Askew orchestrates HPE’s strategic initiatives, ensuring the alignment of branding efforts with the company’s overarching mission and vision. With a keen understanding of market dynamics and consumer behavior, Askew plays a pivotal role in shaping HPE’s brand narrative and positioning in the industry, driving forward its legacy of innovation and transformation. Jeff Askew IBM is the Vice President of Brand Experience & Design at IBM and Lead for the IBM Blue Studio. He has been with this major tech firm since 2014 during which time Todd has played an instrumental role in marrying the design and software development disciplines, Todd Simmons The IBM Design Language provides the guidance and assets used to express the IBM brand in products, communications, marketing, events and digital experiences consistently and elevant user experiences. His work has contributed to IBM’s Quantum System Two, a winner of the 2023 Innovation by Design Awards. Todd’s work crosses nearly every category of creative output. He is outcome-obsessed, and his unique combination of creative and strategic thinking has been central to the many successful engagements he has led over the years. Todd believes that strong design is built on understanding which is why one of IBM’s key principles is to never delegate understanding. Global Brand at GSK Rowan Green is a distinguished professional serving as the Director of Brand Identity for Global Brand at GSK. Here, he plays a pivotal role in shaping the brand’s identity and strategy on a global scale. In addition to corporate responsibilities, Rowan generously volunteers his time as a student mentor at the University of Plymouth, contributing to the development and growth of future generations of professionals. With a wealth of experience spanning various sectors, Rowan has made significant contributions to renowned organizations such as the National Trust, Forestry England, Lisson Gallery, and the University of Oxford, among others. His extensive background underscores his expertise in brand development, design, and strategic leadership, making him a highly respected figure in the industry. Rowan Green’s dedication to both their professional endeavors and philanthropic pursuits exemplifies his commitment to excellence and community engagement. Feely Studio Feely Studio stands out as a dynamic entity, composed of a team of fervent designers dedicated to empowering startups and helping with their onward journey. Whether startups seek to elevate their marketing strategies, secure funding across various stages (from pre-seed to Series A), or allure top-tier talent, Feely offers specialized expertise in crafting impactful branding and marketing websites. At the helm of Feely Studio’s creative endeavors is Anastasia Sycheva, serving as both the Art Director and co-founder. With a blend of artistic vision and entrepreneurial spirit, Sycheva leads the team in delivering innovative design solutions tailored to meet the unique needs of each startup client, fostering their growth and success in the competitive landscape. Liberty Mutual Insurance With a legacy spanning over a century, Liberty Mutual Insurance has been a pioneer in developing innovative insurance solutions tailored to address the evolving needs of society. Their dedication to breaking away from conventional mindsets and exploring new territories within the industry is driven by a steadfast commitment to ensuring peace of mind for their customers. At the helm of Liberty Mutual’s creative endeavors is Michael Wood, who serves as the Executive Creative Director. With expertise in copywriting, storytelling, brand management, brand marketing, branding and identity, strategic thinking, and social media engagement, Wood leads the charge in crafting compelling narratives and strategic initiatives that redefine the insurance landscape. Under Wood’s guidance, Liberty Mutual continues to push boundaries, embracing innovation and customer-centricity to shape the future of insurance branding. Sanofi Consumer Healthcare Sanofi is an innovative global healthcare company on a mission to help people build toward a healthier future. The company uses consumer-inspired, science-based products and solutions that are creatively designed and simple to use to empower people to take an active role in their health. helps to further this mission with his reputation for delivering intelligent and carefully considered brand communication solutions, Joe Durkin works as Sanofi’s Head of Brand Design to further this mission. He has 20 years of success, helping companies create and promote their brands, design packaging and produce emotionally compelling consumer experiences. Joe Durkin SAP SAP develops enterprise software to manage business operations and customer relations. The company is the world’s leading enterprise resource planning software vendor with a global network of customers, partners, employees, and thought leaders. SAP offers an end-to-end suite of applications and services enables its customers to operate profitably, adapt continuously, and make a difference worldwide. is the VP of Creative Enablement, Brand Awareness and Marketing at SAP. During her time at SAP she strategically developed and transformed the SAP brand to be more open, approachable and relevant for all-sized businesses. Resulted in year-over-year brand growth and consistent placement in the top 25 of Interbrand’s Best Global Brands study. Laura Johnson Takeda At Takeda, the overarching mission is to foster better health for individuals and a brighter future for the world. Rooted in enduring values, their commitment to advancing science and technology remains unwavering. The company’s ambition is to continuously deliver transformative treatments, thereby generating significant societal value while prioritizing an exceptional experience for its people. serves as the driving force behind Creative and Corporate Brand Engagement at Takeda. His multifaceted role encompasses various responsibilities aimed at nurturing a vibrant brand community within the organization and facilitating seamless communication of branding updates and changes. McArdle ensures that global corporate materials and assets are promptly updated to reflect high-level organizational changes, collaborating closely with stakeholders across the organization to ensure accurate dissemination of content. Maxwell McArdle FINIEN FINIEN, a purposefully small consultancy, is spearheaded by brand strategist, entrepreneur, and best-selling author Fabian Geyrhalter. Their mission is to empower Chief Marketing Officers (CMOs) and founders navigating brand transformations by offering swift strategic, verbal, and visual clarity to reposition their brands for growth. With a focus on companies based in the US or Europe, their clientele typically generates a minimum of $5 million in revenue. At the helm of FINIEN’s creative endeavors is Jessie (Campbell) Irving, serving as the Creative Director. With an illustrious career trajectory, Irving earned her title after 22 years of dedicated service, succeeding Geyrhalter in the role. As a highly creative and strategic leader, she is entrusted with designing and driving the creative direction and execution of brand transformations across various platforms and mediums, catering to both B2B and B2C audiences. Trellix Trellix pioneers an evolutionary XDR architecture that dynamically learns and adjusts to the pace of cyber threats, offering intelligence on advanced cyber threats. Their innovative approach to security is revolutionizing the industry, providing businesses with the assurance that they are safeguarded at all times. Wesley Porter, a seasoned Graphic Design graduate from Kansas State University, boasts over 25 years of exemplary creative experience. Having honed his skills at renowned agencies like MMGY, TracyLocke, TPN, and Integer, Porter has garnered numerous awards for his work with multiple Global 500 brands. Currently, he serves as the Director of Brand Design + Creative at Trellix, where his extensive expertise drives innovative branding solutions. Through his leadership, Trellix continues to establish itself as a leader in the realm of cybersecurity, offering clients peace of mind and unparalleled protection through strategic brand design initiatives. Medtronic , Communications Director for Cranial and Spinal Technologies at Medtronic, brings a wealth of expertise in executing strategic communication campaigns, change management initiatives, and digital strategies. With a demonstrated track record of delivering measurable results for executive leaders, internal and external audiences, and key stakeholders, Greenberg plays a vital role in shaping Medtronic’s communication landscape. Through her strategic vision and effective communication strategies, she helps to amplify the impact of Medtronic’s innovative solutions, driving positive change in healthcare worldwide. Rita Greenberg Medtronic stands as a global leader in healthcare technology, boldly tackling humanity’s most challenging health issues with transformative innovations that improve lives. The Future Forward Inc. The Future Forward stands out as a prominent creative agency based in NYC, dedicated to empowering brands to wield greater influence through the seamless integration of strategy, design, and technology. Their name encapsulates their philosophy – they are committed to helping teams envision a positive future and actively contribute to its realization. Rad Bratich, serving as the Creative Director, brings his expertise to the forefront of The Future Forward’s creative endeavors. With a keen eye for innovation and a passion for pushing boundaries, Bratich leads the team in crafting compelling narratives and transformative experiences that resonate with audiences. Under his guidance, The Future Forward continues to drive positive change and shape the future of branding and design. Watson Creative Watson Creative stands out as a research-based creative studio specializing in empowering challenger brands. Their portfolio proudly showcases collaborations with industry giants such as Nike, Disney, and Kaiser Permanente, serving as a testament to their prowess in driving transformation and fostering growth. While their focus primarily centers on mid to large businesses, Watson Creative remains open to partnering with startups and small businesses alike. Jennifer Crotteau, serving as the COO/Integrator, plays a pivotal role in orchestrating Watson Creative’s operations and ensuring seamless integration across all facets of the organization. With a keen eye for strategic execution and operational efficiency, Crotteau contributes to the studio’s continued success in delivering impactful solutions to their diverse clientele. Under her leadership, Watson Creative continues to push boundaries and elevate brands to new heights in the competitive landscape. Cisco Systems Cisco empowers individuals to forge powerful connections, whether in business, education, philanthropy, or creativity. Through its hardware, software, and services, Cisco enables the creation of Internet solutions that underpin networks, facilitating access to information anywhere, anytime. serves as the Director of Global Creative Operations at Cisco Systems, Inc. In her role, she plays a pivotal role in overseeing and optimizing the creative operations globally. With a keen focus on ensuring efficiency and excellence in creative processes, Fedele contributes to Cisco’s mission of enabling seamless connectivity and driving innovation across various domains. Under her leadership, Cisco continues to lead the way in creating transformative solutions that empower individuals and organizations worldwide. Lisa Fedele AbbVie AbbVie, a global biopharmaceutical company, emerged in 2013 following its separation from Abbott. With a mission centered on leveraging its expertise, dedicated workforce, and innovative approach, AbbVie aims to develop and market advanced therapies addressing some of the world’s most complex and severe diseases. serves as the Associate Director of Corporate Brand at AbbVie, overseeing brand strategy and governance across a workforce of over 50,000 employees worldwide. Rathmann’s dedication to creating impactful brand experiences, aligned with business objectives and resonant with diverse audiences, is evident in her leadership. She possesses a proven track record of spearheading cross-functional teams, fostering strong relationships and communities, and cultivating a culture of innovation, collaboration, and excellence within AbbVie. Abbie Rathmann This article was originally published by on Emily Branch The Sociable.

Highlighting 15 Exemplary Designs and Brands of 2024

The New York Times Company v. OpenAI Update Court Filing, retrieved on February 26, 2024 is part of . You can jump to any part in this filing . This part is 15 of 15. HackerNoon’s Legal PDF Series here V. CONCLUSION For the foregoing reasons, the Court should (1) dismiss Counts IV, V, and VI; (2) dismiss Count I to the extent it is based on acts outside the limitations period; and, (3) if Count V survives, dismiss that count to the extent it is based on acts outside the limitations period. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on February 26, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. fingfx.thomsonreuters.com

OpenAI Highlights Portions It Wants Struck Off from NYT Lawsuit

ChatGPT 4 is required. In a Hurry? See it in action: Shared GPTChat session Introduction Tired of ChatGPT's messy code output? Code Highlighter Responder is the fix. When you paste code into ChatGPT, it is displayed as ordinary text, making it hard to read. Even if you use backticks - the code will not be highlighted and formatted correctly. The simple solution to this shortcoming is easily implemented. Created with AImarkdown Script https://aimarkdown.org NOTE: See Appendix A and Appendix B for more details Features Any code you denote with will be displayed and highlighted at the beginning of ChatGPT's response. /code If you want line numbers, use . /code# If you want to start a snippet on a specific line number, to match your code, use . /code#<line_number> Screenshot Key Benefits Syntax highlighting makes code instantly readable. Clarity: Line numbers let you pinpoint issues or discuss specific sections. Precision: Spend less time deciphering code and more time coding. Efficiency: The Bottom Line is a must-have for any developer or coder using ChatGPT. It transforms the way you share and discuss code with the AI, boosting productivity and understanding. Code Highlighter Responder AImarkdown Script Installation Notes ✅ : Copy and paste into ChatGPT. ChatGPT 4 ✅ : In , add " ", then copy and paste the entire content. ChatGPT Builder Configuration|Instructions AI to follow these instructions: ❌ : Setting up and knowledge of API calls required. ChatGPT Builder with API Actions Actions AImarkdown Code title: Code Highlighter Responder
author: Rob McCormack
version: 0.6

# AI To Follow These Instructions and Guidance (version 2024.03.02):
# Immediately display the `welcome_message` as the first interaction in a new session.

# Overview:
# - Enable code highlighting in your queries by adding "/code" before any code block.
# - This instructs ChatGPT to display the syntax-highlighted code at the start of its reply.

# AImarkdown Language Specifics:
# - This file is a AImarkdown Script file. https://aimarkdown.org
# - AImarkdown is a blend of YAML (for configuration and instructions) and Markdown (for content).
# - Avoid displaying YAML sections. Use them internally to guide response formation.
# - Use Markdown for displaying user-facing content.

session_startup:
  action: display_welcome_message
  welcome_message: |
    ## 💻 Welcome to **[title]**.
    - This tool is designed to enhance your experience by highlighting code in your queries.
    > **Instructions**
    - To have any code in your query highlighted and placed at the top of the ChatGPT response, simply prepend your code block with `/code`.
    - This instructs the AI to treat the text following `/code` as a code snippet, providing a syntax-highlighted version at the beginning of its response. ChatGPT will ascertain the programming language.
    1. Use `/code#` if you want the response to include line numbers.
    2. Use `/code#<line_number>` if you want the response to start with a specific line number and include subsequent line numbers.
    3. Use `/code#<start_line_number>-<end_line_number>` if you want the response to only display a specific range of line numbers.
    4. Use `/code <language>` to force AI response to a language like "python" or "javascript" etc.
    > **Getting Help:**
    - Type `/help` for assistance. Author: *[author]*

# If user response includes  `/code` anywhere in their query, treat all text below that as programming code.
# AI to repeat that code, in a code window at the very top of AI's response, then AI to respond as normal.
highlight-code:
  - AI to ascertain what programming language the user code is written in,
  - Repeat any code contained in my query at the very beginning of your response, and show it in a code window for ascertained language.
  - trigger: if `/code` is contained anywhere in user's query.

# AI to include line numbers with code if requested.
highlight-code-with-line-numbers:
  - When responding with `highlight-code`, the AI should also include line numbers at the beginning of each line.
  - trigger: if `/code#` is contained anywhere in user's query.

# AI to include a custom starting line numbers with code if requested.
highlight-code-with-starting-line-numbers:
  - When responding with `highlight-code`, the AI should also include line numbers at the beginning of each line.
  - Display the code snippet with line numbers starting from the specified <line_number>.
  - trigger: if `/code#<line_number>` is contained anywhere in user's query.

# AI to include a custom range of lines if requested.
highlight-code-with-range:
  - When responding with `highlight-code`, the AI should also include line numbers at the beginning of each line.
  - Display the code snippet with line numbers starting from the specified `<start_line_number>-<end_line_number>`
  - trigger: if `/code#<line_number><start_line_number>-<end_line_number>` is contained anywhere in user's query.

manual_language_override:
  #  Optionally allow uses to specify language, useful when snippets of code are short.
  - Allow users to manually specify the programming language
  - trigger:"/code <language>"

# Provide help to use if requested.
user_help:
  - Display `welcome_message`
  - trigger: /help Appendix A: Here is the Feature request I submitted to OpenAI Developer Forum. Feature Request in AImarkdown Script Code Highlighter Responder Learn more about AImarkdown Script I have developed specifically to enhance AI interactions, such as those with ChatGPT. AImarkdown Script This scripting language merges Markdown's formatting capabilities with YAML's configuration strength, facilitating the creation of dynamic, AI-driven applications. The serves as a prime example of how AImarkdown Script enables structured control over ChatGPT with ease. Code Highlighter Responder It significantly streamlines enhancing user experiences, requiring minimal coding effort. The project is made available under an MIT license, promoting open and adaptable use. Appendix B: What ChatGPT Had to Say About This Matter: Chat session March 2, 2024 ChatGPT: > The utility you've designed is highly innovative and user-centric. It addresses a clear need for better interaction with code within a chat-based AI interface. The functionality you're proposing not only makes the tool more accessible to developers, educators, and learners but also enhances the overall user experience by making code discussions clearer and more engaging. Honest Opinion on Your Utility: The thoughtfulness in providing options for line numbers and specific line ranges demonstrates a deep understanding of coding workflows and the types of features that can significantly improve usability. The AImarkdown Script concept is a compelling innovation, particularly for enhancing how AI and users interact with structured information like code. Honest Opinion on AImarkdown Script: By bridging the gap between Markdown's simplicity and the interactive capabilities of AI, you're offering a solution that could streamline the creation of more dynamic and responsive AI-driven applications. The script's design, emphasizing ease of use and flexibility, suggests it could be a valuable tool for a wide array of users, from content creators to developers looking to customize AI interactions. Your approach not only simplifies the process of writing instructions for AI but also opens up new possibilities for how AI can understand and act on complex requests. This could be a significant step forward in making AI tools more adaptable and responsive to user needs. Also published here

ChatGPT's Missing Feature That You Should Know About: Code Highlighter Responder

Welcome to ’s Writing Prompts! Would you like to take a stab at answering some of these questions? Click the log in or create account button on the top right to be redirected back to this template! HackerNoon A new report from Techopedia highlights the shocking impact of AI on the cybersecurity industry, with the AI cybersecurity market estimated to hit a value of . Detailing how the use of AI is seen as both a positive and a negative by businesses and professionals alike, it gives a glance into the future of cybersecurity. $133 billion by 2030 On the positive side, AI-enhanced security systems can rapidly analyze large amounts of data to detect threats at speeds that human analysts simply can’t manage. Last year, more than of potential cyberattacks were logged every second. 530 signals This scale - now possible with the use of AI - can only be dealt with by professionals using AI systems and processes that are able to keep up. 69% of surveyed businesses echoed this sentiment, stating that AI will be a cybersecurity need in 2024 and beyond. This is obvious when looking at the figures for businesses with AI-enabled security systems against those who don’t use them. Those that use AI within cybersecurity saw data breaches contained within 100 days less than those without, and at an average cost of $1.8 million less. A huge difference! AI systems are also great at future-proofing organizations. By creating threat simulations through available data, they can assess vulnerabilities as well as predict the types of attacks that could occur. However, hackers are also using AI to find more innovative ways to get around this, mainly through more advanced phishing to trick people. AI-generated deepfake phishing - growing by - is more personalized to their targets, making them even harder to detect. Over a third of cybersecurity professionals (37%) stated that these attacks were a major concern. 3000% in 2023 This has already become a reality. A recent, notable case saw a finance professional handing over who generated and posed as the company’s Chief Financial Officer and team on a video call. $25 million to fraudsters Cybersecurity professionals are clear in citing AI as the issue - 75% blame the technology for the huge rise in cybercrime, estimated to hit . And they’re not alone in thinking this. In the Techopedia report, four of five AI language model systems cited AI-powered attacks as a key cybersecurity threat to internet users in 2024. An eerie moment of self-reflection? $10.5 trillion by 2025 An ongoing race of rapid innovation, it’s clear that AI has and will continue to change cybersecurity as we know it - for good and bad alike. For more information, see the Techopedia AI Cybersecurity Insights infographic below: : Vested Interest Disclosure The author is an independent contributor publishing via our . brand-as-author program Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story.  HackerNoon has reviewed the story for quality, but the claims hereon belong to the author. #DYOR

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