#Big data consulting company

[jcmarchi]

DJ Fang, Co-Founder & Chief Operating Officer at Pure Global – Interview Series

New Post has been published on https://thedigitalinsider.com/dj-fang-co-founder-chief-operating-officer-at-pure-global-interview-series/

DJ Fang, Co-Founder & Chief Operating Officer at Pure Global – Interview Series

DJ Fang is a technology executive and entrepreneur with over 15 years of experience driving digital transformation and innovation across industries, including finance, energy, and healthcare. He has led initiatives for Fortune 500 companies and government agencies, combining business expertise with technical skills in AI, cybersecurity, and cloud infrastructure.

As a serial entrepreneur, Fang has successfully built and scaled businesses, excelling in product development, market strategy, and operational execution.

Pure Global combines real-world experience, AI, and data to create smart and efficient medical device regulatory consulting solutions for more than 30 markets.

Could you share your journey from working with top consulting firms like Deloitte and PwC to becoming the co-founder of Pure Global? What inspired this transition?

My journey to co-founding Pure Global was shaped by two pivotal moments. First, the COVID-19 pandemic threw the world into chaos, forcing individuals, businesses, and governments to re-evaluate how they operated. As a volunteer helping hospitals and schools source PPE, I gained firsthand insight into the challenges people faced adapting to sudden changes in regulations and market access. That experience really opened my eyes to a critical need.

Second, my entrepreneurial drive came into play. I’ve always been drawn to identifying challenges and creating effective solutions, embracing the process of refining and adapting ideas to address changing needs.

Before Pure Global, I had my own big data and cybersecurity consulting firm, and prior to that, I worked at Big Four firms like Deloitte and PwC. I was constantly pushing the boundaries of technology, creating custom solutions for clients facing unique challenges. It was exciting work, always dynamic and demanding.

At Pure Global, I’m tackling similar challenges but with a healthcare focus. We’re helping MedTech companies bring quality products to market faster and more efficiently. It’s incredibly rewarding to apply my skills and experience to make a real difference in this critical industry.

Pure Global was founded during a critical moment in the pandemic. What were the key challenges and opportunities you identified at that time that led to its creation?

During the pandemic, we began by volunteering to help hospitals and schools source PPE. As we worked with global suppliers, we gained insight into the complexities of international trade and regulations. While assisting manufacturers with changing pandemic rules, we also improved our internal processes for efficiency.

Initially, we only supported a few organizations. However, as requests from manufacturers seeking assistance across various countries grew, we identified a clear need – and a market opportunity – for technology to modernize traditional, often inefficient workflows. We saw an opportunity to make a significant impact by developing solutions to address these challenges

Your Resource Center leverages AI to provide real-time regulatory updates and compliance insights. Can you walk us through how the AI algorithms identify and prioritize regulatory changes across 30+ global markets? What challenges did you face in training these models?

Our Global Markets Resource Center serves as a centralized hub for the latest regulatory updates and insights across all major global medical device markets. We’ve built a robust system to gather regulatory data from diverse sources, such as official agency websites, legal databases, and public announcements. This includes web scraping with intelligent parsing to extract data from unstructured formats like PDFs and HTML, as well as using APIs where available.

When clients register their devices in our Pure Certification module, we leverage AI to suggest the most relevant changes and prioritize them for review. AI text embeddings and similarity calculations rank these updates. For example, if you have a ‘portable dialysis machine’ and three related news articles:

Article #1: New guidelines for the disposal PPEs (cosine similarity to product: 0.2)

Article #2: FDA approves a new portable dialysis machine with improved safety features (cosine similarity: 0.8)

Article #3: Cybersecurity vulnerabilities discovered in connected medical devices (cosine similarity: 0.5)

Text embeddings convert all text into numerical representations in a multi-dimensional vector space. Cosine similarity then calculates the distance between these vectors. The higher the cosine similarity, the greater the relevance of the article to the product.

The Translation Manager uses AI to convert technical documents into over 20 languages. How does the system ensure accuracy and cultural relevance in translations for highly regulated markets, and how does it compare to traditional translation methods in terms of speed and compliance reliability?

AI is truly breaking barriers in this regard. From our internal testing with localized regulatory experts, the accuracy of these AI translations exceeds 80%. Combined with our proprietary MedTech-specific multilingual glossaries, we can push this to over 90%, significantly reducing the time required compared to traditional translation methods.

With AI-driven tools like the Translation Manager and Certification Manager, what kind of feedback have you received from clients about their efficiency gains?

Clients have reported significant efficiency gains through the use of our AI-driven tools. Many have experienced reduced translation costs, particularly for high-volume content, thanks to the automation of previously manual tasks. This has not only cut costs but also accelerated workflows.

Additionally, the consistency and flow of translations have improved. Our multilingual translation terminology management ensures consistent language use across all translated materials, which is critical for maintaining brand identity and clarity in technical documentation. Previously, depending on who performed the translation, the flow could differ slightly. With AI-driven translation, however, the consistency and flow are seamless.

In your opinion, how is big data reshaping the MedTech industry, especially in regulatory compliance and market access?

Some exciting developments in the context of big data are as follows:

Data-Driven Decision Making (Market Intelligence): Big data tools provide comprehensive analytics, enabling companies to make informed decisions about market opportunities, patient behavior, product development, market access, and commercial success.

Post-Market Surveillance: Real-world data monitoring can identify safety issues or areas for improvement, leading to faster, more effective post-market surveillance.

Real-World Evidence (RWE): Analyzing large datasets of real-world data (patient records, clinical trials, device usage) can provide evidence of product safety and effectiveness, supporting regulatory submissions and post-market surveillance. However, much of this information still resides within large hospital systems and research institutions, and accessing it remains a challenge.

Cybersecurity:  With the surge in connected medical devices, wearables, and healthcare IoT devices generating vast amounts of data, the attack surface for cybercriminals continues to expand. Sensitive patient information stored in large datasets becomes a prime target for hackers, potentially leading to data breaches that compromise privacy and safety. Then, many healthcare organizations still rely on outdated systems with insufficient cybersecurity measures, increasing the risk.

How do you envision the intersection of AI, cybersecurity, and MedTech evolving in the future?

There will be more personalized options as AI enables the development of medical devices and treatment plans tailored to individual patient needs. By analyzing patient data, including genomics, lifestyle factors, and medical history, AI can optimize device design and functionality. Additionally, AI can accelerate the design and prototyping of medical devices by generating design options, simulating performance, and optimizing for specific requirements, allowing companies to iterate quickly and bring new products to market faster.

Cybersecurity is becoming increasingly emphasized in the MedTech space. This shift comes as regulators recognize its growing importance and transition from a reactive approach—mainly responding to incidents—to a more proactive approach focused on risk management and prevention. As submission requirements for cybersecurity continue to increase in rigor, companies will need to prioritize cybersecurity throughout the entire product development lifecycle, from design to deployment, to ensure the safety and reliability of their devices.

What do you see as the biggest challenges for medical device manufacturers in the next five years, and how does Pure Global aim to address them?

The biggest challenge is that regulatory agencies worldwide are raising the bar for safety, efficacy, and cybersecurity, making it increasingly difficult to keep up with evolving requirements across multiple markets

How Pure Global can help:

AI-Powered Regulatory Intelligence: Pure Global’s AI platform monitors regulatory changes across 30+ markets, offering real-time updates and personalized alerts for compliance.

Streamlined Submission Workflows: AI helps reduce time and costs for regulatory submissions, making the clearance and approval process more efficient.

Market Intelligence: With a comprehensive database covering regulations, product registrations, and clinical trials across 30+ markets, manufacturers can analyze trends, identify opportunities, and assess competition.

What advice would you give to startups and scaleups in the MedTech space looking to navigate complex regulatory landscapes?

Prioritize Regulatory Strategy Early On:

Integrate from the start: Incorporate regulatory considerations into your product development from day one, rather than treating them as an afterthought.

Proactive planning: Establish a clear regulatory strategy early, outlining target markets, device classification, and necessary approvals.

Expert advice: Consult regulatory experts or experienced consultants to understand the specific requirements for your device and target markets.

Stay Agile and Adaptable:

Expect changes: Regulatory landscapes are constantly evolving, so be ready to adapt your strategy as needed.

Flexibility: Keep flexibility in your product development plans to accommodate potential regulatory changes or market requirements.

Thank you for the great interview, readers who wish to learn more should visit Pure Global.

[hari-100]

Transform Your Business with Pixid.ai Data Engineering Services in Australia

Transform Your Business with Pixid.ai Data Engineering Services in Australia

Data engineering is essential for transforming raw data into actionable insights, and Pixid.ai stands out as a leading provider of these services in Australia. Here’s a comprehensive look at what they offer, incorporating key services and terms relevant to the industry

Data Collection and Storage

Pixid.ai excels in big data engineering services in Australia and New zealand  collecting data from various sources like databases, APIs, and IoT devices. They ensure secure storage on cloud platforms or on premises servers, offering flexible cloud data engineering services in Australia tailored to client needs.

Data Processing

Their data processing includes cleaning and organizing raw data to ensure it’s accurate and reliable. This is crucial for effective ETL services in New zealand and Australia (Extract, Transform, Load), which convert raw data into a usable format for analysis.

Data Analysis and Visualization

Pixid.ai employs complex analytical algorithms to detect trends and patterns in data. Their big data analytics company in Australia and New Zealand provides intelligent research and generates visual representations like charts and dashboards to make difficult data easier to grasp. They also provide sentiment analysis services in New zealand and Australia, helping businesses gauge public opinion and customer satisfaction through data.

Business Intelligence and Predictive Analytics

Their robust data analytics consulting services in New zealand and Australia include business intelligence tools for real time performance tracking and predictive analytics to forecast future trends. These services help businesses stay proactive and make data-driven decisions.

Data Governance and Management

Pixid.ai ensures data quality and security through strong data governance frameworks. As data governance service providers in Australia and New zealand they implement policies to comply with regulations, maintain data integrity, and manage data throughout its lifecycle.

Developing a Data Strategy and Roadmap

They collaborate with businesses to develop a comprehensive data strategy aligned with overall business goals. This strategy includes creating a roadmap that outlines steps, timelines, and resources required for successful data initiatives.

Specialized Consulting Services

Pixid.ai offers specialized consulting services in various big data technologies:

Apache Spark consulting services in Australia: Leveraging Spark for fast and scalable data processing.

Data Bricks consulting services in Australia: Utilizing Databricks for unified analytics and AI solutions.

Big data consulting services in Australia: Providing expert guidance on big data solutions and technologies.

Why Choose Pixid.ai?

Pixid.ai’s expertise ensures businesses can leverage their data effectively, providing a competitive edge. Their services span from data collection to advanced analytics, making them a top choice for big data engineering services in Australia and new zealand They utilize technologies like Hadoop and cloud platforms to process data efficiently and derive accurate insights.

Partnering with Pixid.ai means accessing comprehensive data solutions, from cloud data engineering services in Australia to detailed data governance and management. Their specialized consulting services, including Apache Spark consulting services in Australia and Data Bricks consulting services in Australia and new zealand ensure that businesses have the expert guidance needed to maximize their data’s value.

Conclusion

In the competitive landscape of data driven business, Pixid.ai provides essential services to transform raw data into valuable insights. Whether it’s through big data consulting services in Australia and new zealand or data analytics consulting services in new Zealand and Australia, Pixid.ai helps businesses thrive. Their commitment to excellence in data engineering and governance makes them a trusted partner for any business looking to harness the power of their data.

For more information please contact.www.pixid.ai

[techcarrot-dubai]

Unlocking Insights with Cutting-Edge Big Data Analytics Services

In today's data-driven world, businesses generate vast amounts of information every second. Harnessing the power of this data is crucial for making informed decisions, gaining a competitive edge, and driving innovation. techcarrot's Big Data Analytics Services in Dubai and globally are designed to transform raw data into actionable insights, empowering your organization to thrive in the digital era.

Key Features:

·       Data Integration and Aggregation:

Seamlessly integrate data from disparate sources.

Aggregate structured and unstructured data for a comprehensive view.

·       Advanced Analytics:

Employ machine-learning algorithms for predictive analytics.

Identify patterns, trends, and anomalies for strategic decision-making.

·       Scalable Infrastructure:

Utilize robust, scalable infrastructure to handle massive datasets.

Ensure performance and reliability, even with increasing data volumes.

·       Real-time Analytics:

Enable real-time data processing for instant insights.

Quickly respond to changing market conditions and customer behavior.

·       Data Security and Compliance:

Implement robust security measures to protect sensitive information.

Make sure that data protection regulations and industry standards are being followed.

Benefits:

Enhanced Decision-Making:

Make data-driven decisions backed by accurate and timely insights.

Improve strategic planning and resource allocation.

Operational Efficiency:

Streamline processes and operations through data optimization.

Identify and eliminate bottlenecks for improved efficiency.

Competitive Advantage:

Stay ahead of the competition with insights that drive innovation.

Identify emerging trends and market opportunities.

Customer Satisfaction:

Understand customer behavior and preferences.

Personalize offerings and enhance the overall customer experience.

Industries we serve:

Finance: Analyze market trends, manage risks, and optimize investment strategies.

Healthcare: Improve patient outcomes, streamline operations, and enhance healthcare delivery.

Retail: Optimize inventory, personalize marketing, and improve customer engagement.

Manufacturing: Enhance supply chain efficiency, predict maintenance needs, and improve quality control.

Why choose techcarrot for Big Data Analytics Services?

Expertise: Our team of seasoned data scientists and analysts brings extensive experience to the table.

Custom Solutions: Tailored analytics solutions to meet the unique needs of your business.

Scalability: Grow with confidence, knowing our solutions can scale with your evolving data requirements.

Client Success Stories: Discover how our services have transformed businesses in industry.

Get started today! Embrace the power of data with our big Data Analytics Services. Contact us to schedule a consultation and unlock the full potential of your data.

Check out our previous blogs:

Information Technology Consulting Service Middle East

🚀 Empower Your Business with Microservices Application Development Services!

Empowering Your Vision: Leading Mobile App Development Company

[zoondia-ae]

How to Choose the Right Web Application Firewall for Your Needs

What is a web application firewall?

A web application firewall (WAF) is a security solution that protects web applications from a variety of attacks, including cross-site scripting (XSS), SQL injection, and denial-of-service (DoS) attacks. WAFs work by filtering and monitoring HTTP traffic between a web application and the internet. They can be deployed as hardware, software, or cloud-based solutions.

How does a WAF work?

A WAF works by inspecting HTTP requests and responses for malicious patterns. These patterns are typically defined in a set of rules, which are called policies. When a WAF detects a request that matches a policy, it can take one of several actions, such as blocking the request, logging the request, or rewriting the request.

What are the benefits of using a WAF?

WAFs can provide a number of benefits, including:

Increased security: WAFs can help to protect web applications from a variety of attacks, including XSS, SQL injection, and DoS attacks.

Reduced risk of data breaches: WAFs can help to prevent attackers from stealing sensitive data, such as credit card numbers and passwords.

Improved performance: WAFs can help to improve the performance of web applications by filtering out malicious traffic.

Reduced costs: WAFs can help to reduce the costs of security by preventing attacks and data breaches.

What are the different types of WAFs?

There are three main types of WAFs:

Hardware WAFs: These are WAFs that are deployed as physical appliances. They are typically more expensive than other types of WAFs, but they can provide better performance and security.

Software WAFs: These are WAFs that are deployed as software on a web server or application server. They are typically less expensive than hardware WAFs, but they may not provide the same level of performance and security.

Cloud-based WAFs: These are WAFs that are deployed in the cloud. They are typically the most affordable option, but they may not provide the same level of control as other types of WAFs.

How to choose a WAF

When choosing a WAF, there are a number of factors to consider, including:

The size and complexity of your web applications

The types of attacks you are most concerned about

Your budget

Your technical expertise

It is important to consult with a security expert to help you choose the right WAF for your needs.

Conclusion

WAFs are an important part of a comprehensive web application security strategy. By filtering and monitoring HTTP traffic, WAFs can help to protect web applications from a variety of attacks. When choosing a WAF, it is important to consider the size and complexity of your web applications, the types of attacks you are most concerned about, your budget, and your technical expertise.

ENHANCE YOUR WEB APP’S SECURITY WITH ZOONDIA!

Are you searching for a solution to minimize the risk of a data breach on your web application? Partner with Zoondia, a reputable leader in web application development solutions, and unlock boundless possibilities for advancement in software.

Contact us now to uncover how Zoondia stands ready to be your strategic ally in transforming web app development with state-of-the-art software solutions. Let’s work together to craft a more promising tomorrow for your business.

[cloudfountaininc]

Big Data Consulting Services in Boston

As a trusted big data consulting services provider, CloudFountain Inc. Will work to help you organize your big data. Our big data services and consulting experts can help you transform your IT infrastructure and implement big data technologies that help you capture, store and leverage data-driven insights in real time.

[educationisimp0]

Empowering Business Growth: Unleashing the Potential of Data Analytics as a Service

In the fast-paced digital landscape, harnessing the power of data has become paramount for businesses striving to thrive. Discover how Data Analytics as a Service is reshaping industries. Explore the benefits of Analytics as a Service through insights from a leading Data Analytics company. From expert Data Analytics consulting to cutting-edge Data Engineering and from the agility of Data as a Service to the potential of Big Data as a Service, this article delves into the realms of Data Analytics, Data Aggregation, and Business Intelligence. Elevate your understanding of data's transformative role and embrace the future of informed decision-making.

[elsa16744]

What is Data Analytics as a Service (DAaaS): Overview of Next Data

Data Analytics as a Service (DAaaS): How does it Work? The DAaaS approach helps businesses to move away from the ‘one-size-fits-all” approach and integrate a marketplace-based approach, empowering them to choose data analytics services based on their specific needs.

[kattechsystems]

Top Big Data and Data Analytics Trends for Digital Growth In 2023

The year 2023 is set to be a transformative one for the world of Big Data and Data Analytics. The trends that will define this industry are diverse and far-reaching, promising to revolutionize the way businesses approach data analysis and decision-making.

That said, here are some of the top potential trends that could shape the Big Data and Data Analytics industry in 2023:

AI and Machine Learning

AI and machine learning are currently one of the two trends in big data analytics. They enable data-driven decision-making, automation, personalization, and innovation across various domains and industries. AI and machine learning can also augment human capabilities and enhance data quality, reliability, and usability.

Edge Computing

Edge computing is the processing of data at the edge of a network rather than a centralized location. It can reduce latency, bandwidth, and cost, as well as improve security and privacy. Edge computing can also enable real-time analytics and faster response for applications such as IoT, smart cities, autonomous vehicles, and healthcare.

Cloud

The supply of computer services through the internet, including storage, servers, databases, software, and analytics, is known as cloud computing. It can offer scalability, flexibility, accessibility, and cost-effectiveness for big data analytics. The Cloud can also facilitate collaboration, integration, and innovation among different stakeholders and platforms.

DataOps and Observability

DataOps is the application of agile principles and practices to data analytics. It aims to deliver new insights with increasing velocity and quality by streamlining the data lifecycle from collection to consumption. Observability is the ability to monitor the health and performance of data systems and pipelines. It can help identify and resolve issues, optimize resources, and ensure data reliability.

Data Fabric and Data Governance

Data fabric is a unified platform that connects disparate data sources and provides consistent access to data across the organization. It can enable data integration, transformation, discovery, and sharing. Data governance is the set of policies, standards, and processes that ensure the quality, security, privacy, and compliance of data. It can help manage data risks, protect data assets, and align data strategies with business goals.

Data Lakes

Data lakes are repositories that store raw and unstructured data from various sources. They can offer flexibility, scalability, and low cost for big data analytics. Data lakes can also support diverse types of analytics such as descriptive, diagnostic, predictive, prescriptive, and exploratory.

Predictive Analytics

Predictive analytics is the use of data, statistical models, and machine learning to forecast future outcomes or behaviors. It can help businesses anticipate customer needs, optimize operations, reduce risks, and increase revenues. Predictive analytics can also enable proactive actions and recommendations based on data-driven insights.

To sum it up, 2023 promises to be an exciting year for Big Data and Data Analytics. Businesses that embrace these trends and integrate them into their operations are poised to experience significant growth and success in the digital age.

Why choose us?

We at Kat Tech Systems are the top big data analytics companies in the USA. We provide a wide range of services and solutions to our clients across various industries. Our team is experts who have a high level of expertise in data analytics and a strong understanding of our clients’ needs and challenges. We can effectively leverage data analytics to drive business outcomes that are likely to be successful in this highly competitive field.

Our range of IT solutions includes Big Data and Analytics, AI, Cloud Computing, DevOps, IoT, and much more. If you are looking for the best IT consulting firms in Chicago, then we are there for you. Feel free to call us at 001-630 233 8643.

[blockchainbeleaf]

Beleaf Technologies - Blockchain Development Company & Service Provider

Beleaf Technologies is an India-based enterprise blockchain technology solutions and services provider. Our team of experts specialises in developing blockchain technology that is tailored to your company's specific requirements. We understand that each organisation has unique needs, so we work closely with them to understand their requirements and develop custom-built blockchain solutions that can help improve their operations and overall performance. Our blockchain technology is intended to provide businesses with a secure, decentralised, and efficient way to manage their data and transactions. You can reap the benefits of blockchain technology without the hassle of managing and maintaining the infrastructure yourself with our solutions. You can rely on us to provide the best blockchain technology development for your company's needs.

[jcmarchi]

Alibaba Cloud overhauls AI partner initiative

New Post has been published on https://thedigitalinsider.com/alibaba-cloud-overhauls-ai-partner-initiative/

Alibaba Cloud overhauls AI partner initiative

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Alibaba Cloud is overhauling its AI partner ecosystem, unveiling the “Partner Rainforest Plan” during its annual Partner Summit 2024.

The Chinese tech giant’s cloud division has outlined several new initiatives, including an AI partner accelerator programme, enhanced incentives, and a refreshed global strategy for service partners, as it seeks to strengthen its position in the market.

Selina Yuan, President of International Business at Alibaba Cloud Intelligence, said: “At Alibaba Cloud, we believe that collaboration is the key to unlocking innovation and driving growth. Our global partners are not just participants, they are the architects of a new digital landscape in the AI era.

The company’s new AI Alliance Accelerator Programme aims to establish partnerships with 50 AI technology providers and 50 channel partners by 2025. Selected technology partners will receive enhanced technical support, expanded distribution channels, and dedicated AI consulting services, while channel partners will benefit from increased financial incentives for AI-related initiatives.

Alibaba Cloud has also introduced its Revitalised Service Partner Programme, designed to upskill existing partners and cultivate new ones through AI training and empowerment. The programme includes the joint development of Managed Large Language Model Services with service partners, leveraging the company’s generative AI capabilities.

The cloud provider has also committed to extending strategic partnerships with 18 service partners – including prominent names such as Deloitte, Accenture, and Cognizant Worldwide – from its existing pool of 50 global standard service partners.

In various regional developments, Alibaba Cloud has established strategic partnerships across Asia:

Indonesia: The company has partnered with Telkom Indonesia to deliver AI-supported cloud solutions and develop digital talent.

Japan: Information security firm Securai will localise Alibaba Cloud’s Zstack service for the Japanese market.

Thailand: A memorandum of understanding with Yell Group aims to address growing demand for generative AI in the creative media industry.

The company, which currently maintains partnerships with approximately 12,000 organisations worldwide – including industry leaders such as Salesforce, Fortinet, IBM, and Neo4j – has introduced a Synergistic Incentive Programme to foster collaboration between its global technology and channel partners.

“Today, with our revamped global partner ecosystem, we are committed to supporting our global partners to jointly reap the benefits of the AI era and meet the diverse business demands of global customers,” Yuan concludes.

(Photo by Hannah Busing)

See also: Alibaba Marco-o1: Advancing LLM reasoning capabilities

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: ai, alibaba, alibaba cloud, artificial intelligence, partnerships

[mostlysignssomeportents]

The specific process by which Google enshittified its search

I'm touring my new, nationally bestselling novel The Bezzle! Catch me SATURDAY (Apr 27) in MARIN COUNTY, then Winnipeg (May 2), Calgary (May 3), Vancouver (May 4), and beyond!

All digital businesses have the technical capacity to enshittify: the ability to change the underlying functions of the business from moment to moment and user to user, allowing for the rapid transfer of value between business customers, end users and shareholders:

https://pluralistic.net/2023/02/19/twiddler/

If you'd like an essay-formatted version of this thread to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/04/24/naming-names/#prabhakar-raghavan

Which raises an important question: why do companies enshittify at a specific moment, after refraining from enshittifying before? After all, a company always has the potential to benefit by treating its business customers and end users worse, by giving them a worse deal. If you charge more for your product and pay your suppliers less, that leaves more money on the table for your investors.

Of course, it's not that simple. While cheating, price-gouging, and degrading your product can produce gains, these tactics also threaten losses. You might lose customers to a rival, or get punished by a regulator, or face mass resignations from your employees who really believe in your product.

Companies choose not to enshittify their products…until they choose to do so. One theory to explain this is that companies are engaged in a process of continuous assessment, gathering data about their competitive risks, their regulators' mettle, their employees' boldness. When these assessments indicate that the conditions are favorable to enshittification, the CEO walks over to the big "enshittification" lever on the wall and yanks it all the way to MAX.

Some companies have certainly done this – and paid the price. Think of Myspace or Yahoo: companies that made themselves worse by reducing quality and gouging on price (be it measured in dollars or attention – that is, ads) before sinking into obscure senescence. These companies made a bet that they could get richer while getting worse, and they were wrong, and they lost out.

But this model doesn't explain the Great Enshittening, in which all the tech companies are enshittifying at the same time. Maybe all these companies are subscribing to the same business newsletter (or, more likely, buying advice from the same management consultancy) (cough McKinsey cough) that is a kind of industry-wide starter pistol for enshittification.

I think it's something else. I think the main job of a CEO is to show up for work every morning and yank on the enshittification lever as hard as you can, in hopes that you can eke out some incremental gains in your company's cost-basis and/or income by shifting value away from your suppliers and customers to yourself.

We get good digital services when the enshittification lever doesn't budge – when it is constrained: by competition, by regulation, by interoperable mods and hacks that undo enshittification (like alternative clients and ad-blockers) and by workers who have bargaining power thanks to a tight labor market or a powerful union:

https://pluralistic.net/2023/11/09/lead-me-not-into-temptation/#chamberlain

When Google ordered its staff to build a secret Chinese search engine that would censor search results and rat out dissidents to the Chinese secret police, googlers revolted and refused, and the project died:

https://en.wikipedia.org/wiki/Dragonfly_(search_engine)

When Google tried to win a US government contract to build AI for drones used to target and murder civilians far from the battlefield, googlers revolted and refused, and the project died:

https://www.nytimes.com/2018/06/01/technology/google-pentagon-project-maven.html

What's happened since – what's behind all the tech companies enshittifying all at once – is that tech worker power has been smashed, especially at Google, where 12,000 workers were fired just months after a $80b stock buyback that would have paid their wages for the next 27 years. Likewise, competition has receded from tech bosses' worries, thanks to lax antitrust enforcement that saw most credible competitors merged into behemoths, or neutralized with predatory pricing schemes. Lax enforcement of other policies – privacy, labor and consumer protection – loosened up the enshittification lever even more. And the expansion of IP rights, which criminalize most kinds of reverse engineering and aftermarket modification, means that interoperability no longer applies friction to the enshittification lever.

Now that every tech boss has an enshittification lever that moves very freely, they can show up for work, yank the enshittification lever, and it goes all the way to MAX. When googlers protested the company's complicity in the genocide in Gaza, Google didn't kill the project – it mass-fired the workers:

https://medium.com/@notechforapartheid/statement-from-google-workers-with-the-no-tech-for-apartheid-campaign-on-googles-indiscriminate-28ba4c9b7ce8

Enshittification is a macroeconomic phenomenon, determined by the regulatory environment for competition, privacy, labor, consumer protection and IP. But enshittification is also a microeconomic phenomenon, the result of innumerable boardroom and product-planning fights within companies in which would-be enshittifiers try to do things that make the company's products and services shittier wrestle with rivals who want to keep things as they are, or make them better, whether out of principle or fear of the consequences.

Those microeconomic wrestling-matches are where we find enshittification's heroes and villains – the people who fight for the user or stand up for a fair deal, versus the people who want to cheat and wreck to make things better for the company and win bonuses and promotions for themselves:

https://locusmag.com/2023/11/commentary-by-cory-doctorow-dont-be-evil/

These microeconomic struggles are usually obscure, because companies are secretive institutions and our glimpses into their deliberations are normally limited to the odd leaked memo, whistleblower tell-all, or spectacular worker revolt. But when a company gets dragged into court, a new window opens into the company's internal operations. That's especially true when the plaintiff is the US government.

Which brings me back to Google, the poster-child for enshittification, a company that revolutionized the internet a quarter of a century ago with a search-engine that was so good that it felt like magic, which has decayed so badly and so rapidly that whole sections of the internet are disappearing from view for the 90% of users who rely on the search engine as their gateway to the internet.

Google is being sued by the DOJ's Antitrust Division, and that means we are getting a very deep look into the company, as its internal emails and memos come to light:

https://pluralistic.net/2023/10/03/not-feeling-lucky/#fundamental-laws-of-economics

Google is a tech company, and tech companies have literary cultures – they run on email and other forms of written communication, even for casual speech, which is more likely to take place in a chat program than at a water-cooler. This means that tech companies have giant databases full of confessions to every crime they've ever committed:

https://pluralistic.net/2023/09/03/big-tech-cant-stop-telling-on-itself/

Large pieces of Google's database-of-crimes are now on display – so much, in fact, that it's hard for anyone to parse through it all and understand what it means. But some people are trying, and coming up with gold. One of those successful prospectors is Ed Zitron, who has produced a staggering account of the precise moment at which Google search tipped over into enshittification, which names the executives at the very heart of the rot:

https://www.wheresyoured.at/the-men-who-killed-google/

Zitron tells the story of a boardroom struggle over search quality, in which Ben Gomes – a long-tenured googler who helped define the company during its best years – lost a fight with Prabhakar Raghavan, a computer scientist turned manager whose tactic for increasing the number of search queries (and thus the number of ads the company could show to searchers) was to decrease the quality of search. That way, searchers would have to spend more time on Google before they found what they were looking for.

Zitron contrasts the background of these two figures. Gomes, the hero, worked at Google for 19 years, solving fantastically hard technical scaling problems and eventually becoming the company's "search czar." Raghavan, the villain, "failed upwards" through his career, including a stint as Yahoo's head of search from 2005-12, a presiding over the collapse of Yahoo's search business. Under Raghavan's leadership, Yahoo's search market-share fell from 30.4% to 14%, and in the end, Yahoo jettisoned its search altogether and replaced it with Bing.

For Zitron, the memos show how Raghavan engineered the ouster of Gomes, with help from the company CEO, the ex-McKinseyite Sundar Pichai. It was a triumph for enshittification, a deliberate decision to make the product worse in order to make it more profitable, under the (correct) belief that the company's exclusivity deals to provide search everywhere from Iphones and Samsungs to Mozilla would mean that the business would face no consequences for doing so.

It a picture of a company that isn't just too big to fail – it's (as FTC Chair Lina Khan put it on The Daily Show) too big to care:

https://www.youtube.com/watch?v=oaDTiWaYfcM

Zitron's done excellent sleuthing through the court exhibits here, and his writeup is incandescently brilliant. But there's one point I quibble with him on. Zitron writes that "It’s because the people running the tech industry are no longer those that built it."

I think that gets it backwards. I think that there were always enshittifiers in the C-suites of these companies. When Page and Brin brought in the war criminal Eric Schmidt to run the company, he surely started every day with a ritual, ferocious tug at that enshittification lever. The difference wasn't who was in the C-suite – the difference was how freely the lever moved.

On Saturday, I wrote:

The platforms used to treat us well and now treat us badly. That's not because they were setting a patient trap, luring us in with good treatment in the expectation of locking us in and turning on us. Tech bosses do not have the executive function to lie in wait for years and years.

https://pluralistic.net/2024/04/22/kargo-kult-kaptialism/#dont-buy-it

Someone on Hacker News called that "silly," adding that "tech bosses do in fact have the executive function to lie in wait for years and years. That's literally the business model of most startups":

https://news.ycombinator.com/item?id=40114339

That's not quite right, though. The business-model of the startup is to yank on the enshittification lever every day. Tech bosses don't lie in wait for the perfect moment to claw away all the value from their employees, users, business customers, and suppliers – they're always trying to get that value. It's only when they become too big to care that they succeed. That's the definition of being too big to care.

In antitrust circles, they sometimes say that "the process is the punishment." No matter what happens to the DOJ's case against Google, its internal workers have been made visible to the public. The secrecy surrounding the Google trial when it was underway meant that a lot of this stuff flew under the radar when it first appeared. But as Zitron's work shows, there is plenty of treasure to be found in that trove of documents that is now permanently in the public domain.

When future scholars study the enshittocene, they will look to accounts like Zitron's to mark the turning points from the old, good internet to the enshitternet. Let's hope those future scholars have a new, good internet on which to publish their findings.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/04/24/naming-names/#prabhakar-raghavan

[engie-ivy]

Hi! I really like your writing, could you possibly write a fanfic where Remus is a confident gorgeous bastard and Sirius is a flustered mess?

(Hi @arcades-n-academia! You might not even remember this request, with how long it took me to answer. I guess it took some time for a good idea to come to me, and then to find time to actually write it? I would say I hope it's worth the wait, but with how long the wait was that might be pushing it😅 Anyway, without further ado, I present to you:

Confident Gorgeous Remus Lupin and Flustered Mess Sirius Black!)

Being handsome, smart and successful, Remus has his choice of men. So he's allowed to have standards, right? And he has a type, namely confident and intelligent men who know what they are doing. Unfortunately, Sirius Black, easy on the eyes as he might be, is none of those things.

Or so Remus thought.

A New Side

Remus is feeling quite chipper. He's walking down the street carrying two boxes with cake from his favourite bakery, on his way to the office where he worked for the past year.

Remus is a renowned environmental scientist, but he took a break from that line of work to join an environmental law firm. He had wanted to learn more about the legal side of protecting the environment. What arguments are the big corporations using to deny accountability for the pollution they are causing? What data can these environmental lawyers use to prove these corporations are responsible? What evidence of the consequences for the environment is sufficiently compelling to a judge?

In return for learning the ropes of environmental law, Remus has been serving as an expert witness in their cases, and has consulted on scientific matters.

All in all, it has been a good year. Remus had a great time at the company, they made him feel at home and he truly learned a lot. But while he's going to miss the people, hard-working and dedicated to making the world a better place, he's excited to go back to his true passion: scientific research. He's got plenty of ideas, and he's excited to re-join his research team and get started.

Last Friday was officially his last day at the law firm, and since he's still got one week off before he'll take up his old job again, he's dropping by the office today to bring some cake and thank them for the past year.

As Remus pushes open the door, the first person he's greeted by is, unfortunately, Gilderoy Lockhart.

Alright, maybe when he says 'hard-working and dedicated to making the world a better place', that doesn't include everyone.

Lockhart doesn't particularly care about making the world better, he cares more about creating an image of himself as someone who is making the world better. He wants that aesthetic of a handsome, noble lawyer fighting for the good cause. Without doing the actual work, that is. Lockhart is known for doing nothing while taking credit for everything.

They would've kicked him out, if he didn't have a talent for charming people. Especially middle-aged women appear to be quite fond of him. Middle-aged women with too much money looking for a good cause to support. So since Lockhart is so proficient in bringing in donations, they continue to tolerate him.

"Lupin," Lockhart smiles. "Well, isn't today your lucky day."

'Because after today I never have to see you again?' Remus wants to say, but he holds it back. No, he went an entire year without clashing with Lockhart, he's not going to ruin it now. So he forces a smile. "And why is that, Lockhart?"

"Because today is the day you're getting the chance to go on a date with me," Lockhart smirks.

Remus blinks. "Sorry?"

"Yes, you heard that right," Lockhart says, still smirking. "You get to go on a date with me."

"That's… flattering, I suppose, but I'm sorry," Remus shakes his head. "I'm not interested."

Lockhart is silent for a moment, then he lifts his chin and tightens his jaw. "See for yourself then, Lupin. Your loss."

"Remus, you gotta help us out."

Fabian and Gideon have stopped him in the hallway.

"We keep arguing about it," Fabian says.

"So we need you to decide," Gideon adds.

"We usually don't go for the same guy, so this is new to us," Fabian sighs.

"We can't agree upon which one of us gets to ask you out, so we decided to leave it up to you," Gideon shrugs.

"So you need to tell us, Remus," Fabian urges.

"Which one of us would you rather go out with?" They both ask at the same time.

Remus looks from one brother to the other. "I like you both, as good friends."

Fabian cringes and Gideon dramatically places a hand over his heart. "Autch."

"Oh, come on," Remus says. "You can't expect me to choose one of you to date! That's just asking for trouble. Believe me, this is for the best."

"Alright, we normally don't go there, but since it's you, we are willing to make an exception," Fabian says.

"So what about dating both of us at the same time?" Gideon asks.

"Bye, Fabian! Bye, Gideon!" Remus starts to walk away. "Nice catching up with you!"

"You don't know what you'll be missing out on!" Fabian, or maybe Gideon, calls after him.

Benjy keeps nervously fiddling with his tea bag. "So… ehm, I mean, like, we won't see each other at work anymore, and I just thought… I hoped… I wanted to ask… If you don't mind, of course, maybe we could see each other outside of work? You know. Like dinner. If you like to have dinner. With me."

Remus stops from where he had been going through the cabinets of the office kitchen looking for cake forks to look at Benjy. "Oh, Benj… That sounds lovely, really. But truthfully, I'm not looking for anything right now, so it's probably best not to, as I don't want to give you the wrong idea."

It's not exactly true. Remus is quite open to someone storming into his life and sweeping him off of his feet, but Benjy isn't the 'storming in and sweeping you off of your feet'-type. He's the 'carefully shuffling in and awkwardly stammering if he may perhaps attempt to sweep you off of your feet'-type. Not that he isn't a great guy. Remus is sure that there's someone out there who's going to look at Benjy and see him worrying his lip and nervously wringing his hands, and think it's just the cutest thing ever.

But that someone isn't Remus. He needs a man who has a bit more fire in him.

After avoiding an awkward situation with Caradoc Dearborn, by pretending to think the flowers Dearborn gives him are only to thank him for his work in the past year, and Dearborn luckily takes the hint and plays along, Remus runs into Kingsley. At first, Remus is relieved that it's just his work buddy Kingsley, but when Kinsley leans against the wall beside him and gives him that smile, he knows enough.

"No, Kingsley," he says firmly. "No. We are friends. We work well as friends. We are not going to change that."

Kingsley lets his head fall against the wall and lets out a dramatic sigh. "You are a cruel, cruel man, Remus Lupin," he says, but he's smiling as he pushes himself off of the wall. "Well, it was worth a try, but I know a lost cause when I see one."

Remus lets out a relieved sigh as he closes the door to the break room behind him. Mary from Communications, Marlene the Office Manager and Lily from HR look up from their coffee.

"Oh my god!" Mary jumps to her feet and runs up to him. "Cake!" She exclaims, snatching the boxes from his hands.

"Happy to see you too, Mary," Remus says, rolling his eyes.

Mary sits down and flips open one of the boxes. "White chocolate pistachio! You're my hero."

Remus drops down on a chair with a sigh. "Has Mary brought her 'special' brownies to the office again?"

Mary glares at him, swallowing down a mouth full of frosting. "That happened once and it was an accident!" She says. "I took the wrong batch with me."

"I'm not complaining," Marlene smirks. "Best day I've ever had at the office."

"What makes you think the whole office is on drugs?" Lily asks Remus. "Again," she adds, almost as an afterthought.

"Just on the way here," Remus says. "Like, six co-workers asked me out!"

Marlene laughs. "Of course they did!"

Lily leans forward, resting her head on her hands. "Come on, Remus. You must know what's going on."

Remus blinks at her. "I promise you that I really do not."

"This company has a strict No Dating-Policy for its employees," Lily says. "But as of today, you," she points her finger at Remus. "Are no longer an employee."

"Which means…" Remus begins.

"Which means that all those thirsty men who have been lusting after you for the past year can finally shoot their shot!" Mary finishes.

Remus looks at Lily, but she just points at Mary and nods.

"It's true, Rem," Marlene says. "I almost had to ask the janitor to mob the floor in the meeting room after each of your presentations, with how much those guys were drooling!"

"And who can blame them?" Mary says, before Remus can protest. "You, standing there, with that casually tousled hair going on, wearing that button-up with the top buttons undone and your sleeves rolled up to your elbows, talking about critical deposition values, just oozing that whole 'Sexy Professor'-vibe…"

"There's nothing sexy about critical deposition values!" Remus protests, crossing his arms over his chest.

"Say critical deposition values one more time," Mary says, throwing her head back and letting out a fake moan.

Remus flicks a pistachio at her head. "You're a menace."

Mary sticks out her tongue and takes another bite of cake.

Remus shakes his head. "Good god, if that is the case, in retrospect, I'm very thankful for that No Dating-Policy. At least now I only have to endure this awkwardness for one day."

"Two days," Lily corrects. "You have to come to the office party this Friday!"

Remus raises his eyebrows. "Party? Are we celebrating?"

A huge grin appears on Lily's face. "Indeed we are! We won the case against Exxon!" She cheers.

Remus stares at her. "The case against… No way!"

"Way!"

Remus laughs out loud. "Oh my god! That's amazing! I can hardly believe it! I thought that case was mostly symbolic? That we didn't have a chance at actually winning?"

"So did I!" Lily exclaims.

"So did everyone!" Mary exclaims.

Marlene shakes her head with a huge grin on her face. "But don't tell Sirius he can't do something!"

"Wait," Remus says. "Back up. Sirius? As in Sirius Black?"

"No, Remus. One of the many other Siriuses that work here," Lily deadpans. "Yes, Sirius Black! Why does that surprise you?"

"No reason, just…" Remus shrugs awkwardly. "Well, he isn't exactly the sharpest tool in the shed, is he?"

All three girls stare at him like he has grown two heads.

"Remus," Lily eventually manages to say. "I don't know what kind of tools you have in your shed, but in most sheds, they don't come much sharper than Sirius Black. He graduated top of his year from Harvard Law, he takes on the most challenging cases from all our lawyers, and still manages to win more cases than any of the other lawyers, our biggest clients almost always request for him by name to represent them, and he receives about five offers per week from corporate offices willing to pay him at least five times what we can afford." She shakes her head. "We're lucky he's so dedicated to the cause, otherwise we would never have been able to keep him.

Remus blinks. "Really? Okay. Wow. That's… not what I expected."

The first time Remus saw Black, their conversation went something like this:

"Hi! I'm your new colleague, Remus Lupin. Nice to meet you!"

"Uh, yeah."

"So… what kind of work do you do?"

"I… ehm, I work for an environmental law firm."

"...Yes. I know. We're colleagues. I mean what sort of work do you do within the firm?"

"Oh, yes, I work in environmental law. I do law work. For… the environment."

"Right."

After that conversation, Remus had concluded that, despite what his first name might suggest, Sirius Black wasn't exactly a bright light. Their following conversations had only confirmed his suspicions.

"Hey Black. That's quite a stack of papers you're carrying. Big case?"

"Oh, no, just a normal briefcase fits fine."

"Oh, Black, can I get your opinion on the presentation I gave at the meeting this morning? What did you think of the slides?"

"I loved them! They were nice!"

"Yeah, thanks, but were they clear enough?"

"Oh, yes! I could see them very well. With the blue background and white letters. Very clear."

"No, I mean… You know what, nevermind."

Remus had assumed that Black, not being the sharpest mind, must be some sort of an assistant to the lawyers, searching files, copying documents, writing minutes, that sort of work.

Remus also thought, and he's rather ashamed to admit this, that maybe they employed Black because of his father, the infamous cut-throat corporate lawyer Orion Black. Maybe they thought that Orion Black would go a bit more easy on them when meeting them across the courtroom if his son worked for them. Though if that was the case, it was to no avail. If anything, Orion Black seems even more determined to take their firm down any chance he gets.

Remus even thought, and yes, he's even more ashamed to admit this, that the only reason they kept Black around could be because the man is so easy on the eyes.

"So, what made you think Sirius is a dummy?" Mary asks cheerfully.

"I've been trying to get to know him, but it's hard to learn more about someone when they can't hold a bloody conversation," Remus says defensively. "I swear, every time I try to talk to him, the guy can barely string a sentence together!"

The girls are silent for a moment. Then they all burst out laughing.

"Oh my god," Marlene says, wiping tears from her eyes. "I can't believe it. Sirius Black, with his infamous sharp tongue, who always has a retort for everything and can make even the most ruthless corporate lawyer tremble with fear, finally at a loss for words, because of a cute guy!" She laughs again. "I'm never going to let him hear the end of this, I swear!"

"As any good friend should," Mary says approvingly.

Remus looks puzzled.

"Come on, Remus," Lily grins. "With your experience from today, I think it's pretty clear why Sirius’ brain turns to mush around you!"

"So," Remus says slowly. "Black is actually both very intelligent and very into me?"

"He sure is."

Remus sits back on his chair and takes a sip of his coffee. "Interesting."

Remus is hiding in a corner. Not how he usually acts at parties, but he's got a very good reason. Two very good reasons actually.

First, it's so that he won't continuously get hit on, with people making flirtatious comments, bringing him drinks or making not-so-subtle suggestions of what they could do after the party now that they're no longer co-workers.

Second, it's so he can observe Sirius Black without Sirius Black knowing he's observing him.

Because Remus is intrigued.

Sure, he did find Black attractive. No one who sees him can deny that he's a good-looking man. But Remus never considered him as someone he'd potentially want to date.

Remus likes intelligent men. Maybe that's pretentious, but it's just how it is. He's attracted to men whom he can have stimulating conversations with, who challenge him and keep him on his toes, who he can share ideas with. Black seemed to be none of those things, so Remus had never looked at him like that.

Tonight, though, Remus is looking.

Black is, of course, the star of the evening. The whole party is to celebrate his achievement, after all. He looks stunning in his dress shirt and his long hair tied up. Everybody wants to talk to the man of the moment, and Black is making rounds, going from group to group, smiling brightly and making easy conversation with everyone. He looks confident and at ease, oozing charisma and competence.

Remus hadn't felt any particular way about the fidgety Sirius Black stumbling over his words, but this Sirius Black… This is a Sirius Black he would like to see more of. There's just something incredibly sexy about a confident man who knows what he's doing, and knows he's doing it well.

Black is currently chatting to the Bones-siblings– Amelia and Edgar are from the prestigious Bones family, known for their philanthropy and welfare work, and both are highly educated and strongly dedicated–, and Peter Petttigrew and Emmeline Vance. Vance is a tall, blond woman, who works for a pharmaceutical company and with whom they once had to negotiate a settlement with. Peter was quite infatuated with her, and keeps inviting her to these types of events, hoping to get with her, though everyone can see Vance has no real interest in him besides his connections.

Remus doesn't know whether Vance likes to play devil's advocate, or whether she's really defending her beliefs, but she's always taking opposing stances and arguing with everyone from the firm. Remus supposes she thinks having a different opinion makes her special and interesting, by showing she's not like the rest of them naive ideologists, but Remus disagrees. Sometimes, having a different opinion just makes you wrong.

Vance brushes her long, blond hair back. "You drive a motorcycle, right?" She asks Black. "Which means you need fuel. You can attack Exxon, but at the same time, you're one of the consumers creating the demand they're providing." She crosses her arms over her chest, looking quite smug.

Black arches an eyebrow. "I try to make the world a better place, whilst not being perfect myself, yes."

"Well, doesn't that make you…"

"A hypocrite?" Black finishes.

Vance shrugs.

"No one can do everything right. If trying to do good while you know you will sometimes get it wrong makes you a hypocrite, then not even trying to do any good only because you know you can't do everything makes you a cynic." Black crosses his arms over his chest and looks Vance in the eyes. "And then I'd rather be a hypocrite than a cynic."

"And you think bringing a company to the verge of bankruptcy with such an erratic fine is 'doing good'?" Vance asks. "If you take speeding, for instance, people don't speed because they know what fine they'll have to pay when they do. The fine Exxon has been given, however, is unprecedented. Therefore, Exxon couldn't have taken it into account when deciding upon their actions. Therefore, it is unfair." She looks quite pleased with herself.

Black does not look impressed with her argumentation, though. "We fine Exxon because we want them to not pour a gallon of crude oil over a baby seal," he says. "Not because we want to enable them to conduct a detailed cost-benefit-analysis on the strategy of pouring a gallon of crude oil over a baby seal! If they don't like that the consequences are unpredictable, good. It's a punishment, they're supposed to not like it."

"But you can't let such a vital company face the threat of bankruptcy!" Vance persists, clearly trying to get under Black's skin.

Black shrugs. "You're the one who started drawing parallels with criminal law. Alright, but then let's be consistent. What's the highest price someone can pay for the worst crime? It's their actual life. Now, Exxon has destroyed ecosystems, destroyed the lives of hundreds of people, and killed countless wildlife. It doesn't get much worse than that, so what would be the corporate equivalent of having to pay with your life? Bankruptcy indeed, if you follow your own logic."

"But do you really think Exxon is going to pay up?" Edgar Bones asks carefully. "I mean, Exxon has got an whole army of the best lawyers at their disposal. They can keep appealing the verdict to a higher and higher court, and keep stalling the process. The plaintiffs will be broke and forced to give up any further legal proceedings before they ever see a dime."

"If Exxon wants to drag this process out for years," Black replies instantly. "Then I will be breathing down their neck every single day for as long as it lasts and make sure they won't get a moment of rest from this case until they pay up! If we let them get away with this, simply because they have more means, it'll send a message to all companies like them that they can do whatever they want and no one will hold them accountable."

"But they won't be able to afford your services anymore."

"I don't want any money, not until the plaintiffs have been paid what they are due," Black says passionately, balling his fists.

"I suppose it's good exposure for your brand," Vance contemplates. "Being the activist lawyer engaged in a legal battle with Exxon."

Black gives her a hard look. "Some things aren't about money, or exposure. Some things just matter."

Remus stares at Black. That unwavering conviction, that fierce determination… It does something to him. Seeing that burning passion in his eyes, it makes something stir in Remus' stomach.

Remus chugs the rest of his his wine and places the empty glass on a passing waitress' tray, before making his way over to the group.

"Professor Lupin!" Vance says, batting her eyelashes at him. "Always good to see you."

"Hi Remus," Edgar Bones says warmly, giving Remus a quick once-over. "Glad you decided to come tonight."

"Yes, hi," Remus says, without taking his eyes off of Black, whose mouth is opening and closing like a fish without any words coming out. "Could I steal the man of the moment for a bit?" He asks, winking at Black. "To congratulate him on his big win."

Vance looks from Remus to Black and back. "Figures," she mumbles, before brushing her blond hair back and stalking off.

"Oh, I was hoping…" Edgar Bones begins.

"Of course, Remus," Amelia Bones interrupts, grabbing her brother's arm and dragging him away. "Come on, Ed. Let them have a moment."

"I hope I wasn't interrupting anything important?" Remus asks sweetly, smiling at Black.

Black's face flushes. "No! No, nothing important! Just talking about… how you should be a hypocrite, and how you can calculate the benefits of pouring oil on a baby seal, and how my clients will go bankrupt paying me…"

Remus arches an eyebrow.

Black cringes at himself, and covers his eyes with his hand, groaning. "Oh god, I swear… I swear, I'm actually smart!" He says. "I have more than two brain cells! I swear I do! The rest just somehow… switches off when it comes to you."

Remus throws his head back and lets out a genuine laugh. "Well, I guess it's good then that I'm not some corporate lawyer on the other side of the courtroom," he teases.

"It wouldn't have mattered then," Black mutters, crossing his arms over his chest.

Remus frowns. "How so?"

"I like how dedicated you are to your research," Black explains. "It's not just a job to you, you actually care. The way you talk about an exciting new research idea," a spark appears in Black's eyes as he talks. "With that contagious excitement, and always so hopeful, no matter how bad the world can be, that we can make it better. There's a fire and a passion to you." Black seems to realize he's been rambling, and he shrugs awkwardly. "I hardly would've been impressed to the point of my brain shutting down if you had been using that fire and passion to defend some bank's right to invest their client's money in cutting down the rainforest."

Remus stares at him.

He was not expecting this. His face feels warm, and- God, is he blushing? He can't remember the last time he blushed!

He thought Sirius liked him because he's handsome and successful. Many people do. But Sirius has seen him, and likes him for the kind of person he is. Remus feels something stir again, but this time not in his stomach, but higher, in the chest-area.

He gives Sirius a warm smile. "Thank you," he says sincerely, and then he laughs. "What can I say? Some things just matter."

Sirius just looks at him for a moment, before snapping out of it. "Oh, it's nothing." He wants to make a dismissive gesture with his hand, but he has forgotten he's holding a glass of red wine, and ends up throwing it all over his shirt. "Shite!" He curses, wiping his hands over his shirt, only making it worse. "Dammit, dammit! God, I'm such a bloody pillock!"

Remus looks on with a fond smile. Yes, it's going to take a lot of effort to bring out that confident, competent Sirius Black around him, but Remus has the feeling that it's going to be worth it.

[cyberstudious]

An Introduction to Cybersecurity

I created this post for the Studyblr Masterpost Jam, check out the tag for more cool masterposts from folks in the studyblr community!

What is cybersecurity?

Cybersecurity is all about securing technology and processes - making sure that the software, hardware, and networks that run the world do exactly what they need to do and can't be abused by bad actors.

The CIA triad is a concept used to explain the three goals of cybersecurity. The pieces are:

Confidentiality: ensuring that information is kept secret, so it can only be viewed by the people who are allowed to do so. This involves encrypting data, requiring authentication before viewing data, and more.

Integrity: ensuring that information is trustworthy and cannot be tampered with. For example, this involves making sure that no one changes the contents of the file you're trying to download or intercepts your text messages.

Availability: ensuring that the services you need are there when you need them. Blocking every single person from accessing a piece of valuable information would be secure, but completely unusable, so we have to think about availability. This can also mean blocking DDoS attacks or fixing flaws in software that cause crashes or service issues.

What are some specializations within cybersecurity? What do cybersecurity professionals do?

incident response

digital forensics (often combined with incident response in the acronym DFIR)

reverse engineering

cryptography

governance/compliance/risk management

penetration testing/ethical hacking

vulnerability research/bug bounty

threat intelligence

cloud security

industrial/IoT security, often called Operational Technology (OT)

security engineering/writing code for cybersecurity tools (this is what I do!)

and more!

Where do cybersecurity professionals work?

I view the industry in three big chunks: vendors, everyday companies (for lack of a better term), and government. It's more complicated than that, but it helps.

Vendors make and sell security tools or services to other companies. Some examples are Crowdstrike, Cisco, Microsoft, Palo Alto, EY, etc. Vendors can be giant multinational corporations or small startups. Security tools can include software and hardware, while services can include consulting, technical support, or incident response or digital forensics services. Some companies are Managed Security Service Providers (MSSPs), which means that they serve as the security team for many other (often small) businesses.

Everyday companies include everyone from giant companies like Coca-Cola to the mom and pop shop down the street. Every company is a tech company now, and someone has to be in charge of securing things. Some businesses will have their own internal security teams that respond to incidents. Many companies buy tools provided by vendors like the ones above, and someone has to manage them. Small companies with small tech departments might dump all cybersecurity responsibilities on the IT team (or outsource things to a MSSP), or larger ones may have a dedicated security staff.

Government cybersecurity work can involve a lot of things, from securing the local water supply to working for the big three letter agencies. In the U.S. at least, there are also a lot of government contractors, who are their own individual companies but the vast majority of what they do is for the government. MITRE is one example, and the federal research labs and some university-affiliated labs are an extension of this. Government work and military contractor work are where geopolitics and ethics come into play most clearly, so just… be mindful.

What do academics in cybersecurity research?

A wide variety of things! You can get a good idea by browsing the papers from the ACM's Computer and Communications Security Conference. Some of the big research areas that I'm aware of are:

cryptography & post-quantum cryptography

machine learning model security & alignment

formal proofs of a program & programming language security

security & privacy

security of network protocols

vulnerability research & developing new attack vectors

Cybersecurity seems niche at first, but it actually covers a huge range of topics all across technology and policy. It's vital to running the world today, and I'm obviously biased but I think it's a fascinating topic to learn about. I'll be posting a new cybersecurity masterpost each day this week as a part of the #StudyblrMasterpostJam, so keep an eye out for tomorrow's post! In the meantime, check out the tag and see what other folks are posting about :D

[techcarrot-dubai]

techcarrot – Big Data Solutions Provider Company

techcarrot is a trusted partner in revolutionizing the way companies harness and utilize Big Data. With a proven track record of excellence, we are the driving force behind businesses that thrive in the data-driven era. A few of our strengths include:

Unparalleled Expertise: Our team of data scientists, engineers, and analysts leverage years of industry experience to tailor solutions that fit your unique needs. We cover everything from data collection and storage to advanced analytics and actionable insights.

Innovative Solutions: At techcarrot we understand that every business has its own challenges and goals. That's why we craft innovative, customized strategies that unleash the potential of your data. Whether it is predictive modeling, real-time analytics, or AI-powered insights, our solutions are designed to empower your decision-making process.

Data Security: We recognize that data is critical to your business, and its security is non-negotiable. With cutting-edge encryption, robust access controls, and vigilant monitoring, we ensure your data remains safe from threats.

Scalability: As your business grows your data also increases. Our Big Data solution & consulting services are built with scalability in mind, allowing you to seamlessly expand your data capabilities. We have the infrastructure and expertise to support data even in terabytes or petabytes.

Global Impact: Our solutions have transformed businesses across industries, enabling them to make smarter decisions, optimize operations, and drive innovation. Join our network of satisfied clients who have turned their data into a strategic asset.

Collaborative Approach: We work closely with you to understand your challenges, goals, and aspirations. Through open communication and collaboration, we ensure that our solutions align perfectly with your vision.

Don't miss out on the Big Data revolution. Choose techcarrot as your partner for all your data requirements as we are the best Big Data Solution Providers Company. Contact us today!

[zoondia-ae]

Generative AI: The Future of Creativity and Innovation

What is Generative AI?

Generative AI is a type of artificial intelligence (AI) that is able to create new content, such as text, images, or music. This is accomplished by acquiring knowledge from an extensive dataset of pre-existing material. For example, a generative AI model trained on a dataset of images of cats could be used to generate new images of cats.

Generative AI is rapidly advancing and has numerous promising applications, including:

Generating creative content: Generative AI can be used to create new forms of art, music, and literature. For example, the DALL-E 2 model can be used to generate images from text descriptions, such as "a cat riding a unicycle on a beach."

Tailoring experiences: Generative AI can be applied to customize user experiences. For example, a generative AI model could be used to generate personalized recommendations for movies or products.

Improving efficiency: Generative AI can be used to improve the efficiency of tasks. For example, a generative AI model could be used to generate code or translate languages.

How does generative AI work?

Generative AI models are typically trained on a large dataset of existing content. The model learns to identify patterns in the data and then use those patterns to generate new content.

There are many different ways to train a generative AI model. A common method involves employing deep learning, which utilizes artificial neural networks to acquire knowledge from data.

What are the benefits of generative AI?

Generative AI has many potential benefits, including:

Creativity: Generative AI can help us create new and innovative forms of content.

Personalization: Generative AI can help us personalize experiences for users.

Efficiency: Generative AI can help us improve the efficiency of tasks.

Discovery: Generative AI can help us discover new patterns and insights in data.

What are the challenges of generative AI?

Generative AI also has some challenges, including:

Bias: Generative AI models can be biased, reflecting the biases that exist in the data they are trained on.

Safety: Generative AI models can be used to generate harmful or misleading content.

Regulation: There is a lack of regulation governing the development and use of generative AI.

The future of generative AI

Generative AI is a swiftly expanding field with a multitude of potential uses. As the technology continues to develop, we can expect to see even more innovative and creative uses of generative AI in the years to come.

Here are some of the ways that generative AI is expected to be used in the future:

Generating realistic synthetic data: Generative AI can be used to generate realistic synthetic data, which can be used to train other AI models or to test the robustness of AI systems.

Creating new forms of art and entertainment: Generative AI can be used to create new forms of art and entertainment, such as music, movies, and video games.

Personalizing products and services: Generative AI can be used to personalize products and services for users, such as recommending products or tailoring news feeds.

Improving medical diagnostics: Generative AI can be used to improve medical diagnostics by generating images of diseases or creating simulations of medical procedures.

Designing new products and materials: Generative AI can be used to design new products and materials, such as new drugs or new types of fabric.

Generative AI is a powerful new technology with the potential to revolutionize many industries. As the technology continues to develop, we can expect to see even more innovative and creative uses of generative AI in the years to come.

START YOUR SOFTWARE DEVELOPMENT JOURNEY WITH ZOONDIA TODAY

Generative AI is an emerging field of AI that is changing the way we create software. By automating tasks, generating insights from data, and creating new experiences for users, generative AI can help businesses to create software that is more innovative, efficient, and effective.

If you are looking for a custom software development company that can help you leverage the power of generative AI, then Zoondia is the perfect choice for you. We understand that every business is different, and we will work with you to create a solution that is right for you. Contact us today to learn more about how we can help you create the software of your dreams.

[cloudfountaininc]

Big data analytics is essential for businesses and organizations to identify opportunities for better operations, smart strategies, extremely satisfied customers, and higher profits. With the help of 5v's volume, velocity, variety, veracity and value, big data consulting services providers can improve the organization's decision-making and can be a crucial weapon to maintain the industrial standing.