#Big data consulting company

[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

[jcmarchi]

IBM and Tech Mahindra launch trustworthy AI with watsonx

New Post has been published on https://thedigitalinsider.com/ibm-and-tech-mahindra-launch-trustworthy-ai-with-watsonx/

IBM and Tech Mahindra launch trustworthy AI with watsonx

.pp-multiple-authors-boxes-wrapper display:none; img width:100%;

Tech Mahindra, a global provider of technology consulting and digital solutions, has collaborated with IBM to help organisations sustainably accelerate generative AI use worldwide.

This collaboration combines Tech Mahindra’s range of AI offerings, TechM amplifAI0->∞, and IBM’s watsonx AI and data platform with AI Assistants.

Customers can now combine IBM watsonx’s capabilities with Tech Mahindra’s AI consulting and engineering skills to access a variety of new generative AI services, frameworks, and solution architectures. This enables the development of AI apps in which organisations can use their trusted data to automate processes. It also provides a basis for businesses to create trustworthy AI models, promotes explainability to help manage risk and bias, and enables scalable AI adoption across hybrid cloud and on-premises environments.

According to Kunal Purohit, Tech Mahindra’s chief digital services officer, organisations focus on responsible AI practices, and incorporating generative AI technologies to revitalise enterprises. 

“Our work with IBM can help advance digital transformation for organisations, adoption of GenAI, modernisation, and ultimately foster business growth for our global customers,” Purohit added.

To further enhance business capabilities in AI, Tech Mahindra has established a virtual watsonx Centre of Excellence (CoE), which is already operational. This CoE functions as a co-innovation centre, with a dedicated team tasked with maximising synergies between the two companies and producing unique offerings and solutions based on their combined capabilities.

The collaborative offerings and solutions developed through this partnership could help enterprises achieve their goals of constructing machine learning models using open-source frameworks while also enabling them to scale and accelerate the impact of generative AI. These AI-driven solutions have the potential to aid organisations enhance efficiency and productivity responsibly. 

Kate Woolley, GM of IBM Ecosystem, emphasised the collaboration’s potential, adding that generative AI may serve as a catalyst for innovation, unlocking new market opportunities when built on a foundation of explainability, transparency, and trust. 

Woolley said: “Our work with Tech Mahindra is expected to expand the reach of watsonx, allowing even more customers to build trustworthy AI as we seek to combine our technology and expertise to support enterprise use cases such as code modernisation, digital labour, and customer service.”

This collaboration aligns with Tech Mahindra’s continuous endeavour to transform enterprises with advanced AI-led offerings and solutions, including their recent additions like Vision amplifAIer, Ops amplifAIer, Email amplifAIer, Enterprise Knowledge Search offering, Evangelize Pair Programming, and Generative AI Studio.

It is worth mentioning that the two companies have previously collaborated. Earlier this year, Tech Mahindra announced the opening of a Synergy Lounge in conjunction with IBM on the company’s Singapore campus. This Lounge seeks to accelerate digital adoption for APAC organisations. It aids in operationalising and leveraging next-generation technologies such as AI, intelligent automation, hybrid cloud, 5G, edge computing, and cybersecurity.

Beyond Tech Mahindra, IBM watsonx has been used in other collaborations to speed up the deployment of generative AI. Also happened early this year, the GSMA and IBM announced a new partnership to support the use and capabilities of generative AI in the telecom industry by launching GSMA Advance’s AI Training program and the GSMA Foundry Generative AI program.

In addition, there is a digital version of the program that covers both the commercial strategy and technology fundamentals of generative AI. This initiative uses IBM watsonx to provide hands-on training for architects and developers seeking in-depth practical generative AI knowledge.

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, artificial intelligence, customer service, generative ai, ibm, ibm watson

[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.

[sanskarjaiswal]

The big data analytics market is marching at a faster pace.  

Businesses are estimated to have spent $215 billion in 2021 on designing big data and business analytics solutions. Due to this, the demand for data analytics professionals is also on the rise. U.S. Bureau of Labor Statistics researchers highlighted the growth of 31% in the field of data science through 2030.  

[qmoniqs]

Qmoniqs Software is prominent for providing outstanding IT Services Companies in Gurugram, which are obviously affordable and advantageous. Apart from that, we have excellent tools for developing application Software. Our business software maker team has the expertise and works mindfully.

[jcmarchi]

Microsoft recruits former OpenAI CEO Sam Altman and Co-Founder Greg Brockman

New Post has been published on https://thedigitalinsider.com/microsoft-recruits-former-openai-ceo-sam-altman-and-co-founder-greg-brockman/

Microsoft recruits former OpenAI CEO Sam Altman and Co-Founder Greg Brockman

.pp-multiple-authors-boxes-wrapper display:none; img width:100%;

AI experts don’t stay jobless for long, as evidenced by Microsoft’s quick recruitment of former OpenAI CEO Sam Altman and Co-Founder Greg Brockman.

Altman, who was recently ousted by OpenAI’s board for reasons that have had no shortage of speculation, has found a new home at Microsoft. The announcement came after unsuccessful negotiations with OpenAI’s board to reinstate Altman.

I deeply regret my participation in the board’s actions. I never intended to harm OpenAI. I love everything we’ve built together and I will do everything I can to reunite the company.

— Ilya Sutskever (@ilyasut) November 20, 2023

Microsoft CEO Satya Nadella – who has long expressed confidence in Altman’s vision and leadership – revealed that Altman and Brockman will lead Microsoft’s newly established advanced AI research team.

Nadella expressed excitement about the collaboration, stating, “We’re extremely excited to share the news that Sam Altman and Greg Brockman, together with colleagues, will be joining Microsoft to lead a new advanced AI research team. We look forward to moving quickly to provide them with the resources needed for their success.”

I’m super excited to have you join as CEO of this new group, Sam, setting a new pace for innovation. We’ve learned a lot over the years about how to give founders and innovators space to build independent identities and cultures within Microsoft, including GitHub, Mojang Studios,…

— Satya Nadella (@satyanadella) November 20, 2023

The move follows Altman’s abrupt departure from OpenAI. Former Twitch CEO Emmett Shear has been appointed as interim CEO at OpenAI.

Today I got a call inviting me to consider a once-in-a-lifetime opportunity: to become the interim CEO of @OpenAI. After consulting with my family and reflecting on it for just a few hours, I accepted. I had recently resigned from my role as CEO of Twitch due to the birth of my…

— Emmett Shear (@eshear) November 20, 2023

Altman’s role at Microsoft is anticipated to build on the company’s strategy of allowing founders and innovators space to create independent identities, similar to Microsoft’s approach with GitHub, Mojang Studios, and LinkedIn.

Microsoft’s decision to bring Altman and Brockman on board coincides with the development of its custom AI chip. The Maia AI chip, designed to train large language models, aims to reduce dependence on Nvidia.

While Microsoft reassures its commitment to the OpenAI partnership, valued at approximately $10 billion, it emphasises ongoing innovation and support for customers and partners.

As Altman and Brockman embark on leading Microsoft’s advanced AI research team, the industry will be watching closely to see what the high-profile figures can do with Microsoft’s resources at their disposal. The industry will also be observing whether OpenAI can maintain its success under different leadership.

(Photo by Turag Photography on Unsplash)

See also: Amdocs, NVIDIA and Microsoft Azure build custom LLMs for telcos

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 Digital Transformation Week.

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

Tags: ai, artificial intelligence, greg brockman, maia chip, microsoft, openai, sam altman, satya nadella

[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

[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.