#generative ai for telecom

[brillioitservices]

The Generative AI Revolution: Transforming Industries with Brillio

The realm of artificial intelligence is experiencing a paradigm shift with the emergence of generative AI. Unlike traditional AI models focused on analyzing existing data, generative AI takes a leap forward by creating entirely new content. The generative ai technology unlocks a future brimming with possibilities across diverse industries. Let's read about the transformative power of generative AI in various sectors: 

1. Healthcare Industry: 

AI for Network Optimization: Generative AI can optimize healthcare networks by predicting patient flow, resource allocation, etc. This translates to streamlined operations, improved efficiency, and potentially reduced wait times. 

Generative AI for Life Sciences & Pharma: Imagine accelerating drug discovery by generating new molecule structures with desired properties. Generative AI can analyze vast datasets to identify potential drug candidates, saving valuable time and resources in the pharmaceutical research and development process. 

Patient Experience Redefined: Generative AI can personalize patient communication and education. Imagine chatbots that provide tailored guidance based on a patient's medical history or generate realistic simulations for medical training. 

Future of AI in Healthcare: Generative AI has the potential to revolutionize disease diagnosis and treatment plans by creating synthetic patient data for anonymized medical research and personalized drug development based on individual genetic profiles. 

2. Retail Industry: 

Advanced Analytics with Generative AI: Retailers can leverage generative AI to analyze customer behavior and predict future trends. This allows for targeted marketing campaigns, optimized product placement based on customer preferences, and even the generation of personalized product recommendations. 

AI Retail Merchandising: Imagine creating a virtual storefront that dynamically adjusts based on customer demographics and real-time buying patterns. Generative AI can optimize product assortments, recommend complementary items, and predict optimal pricing strategies. 

Demystifying Customer Experience: Generative AI can analyze customer feedback and social media data to identify emerging trends and potential areas of improvement in the customer journey. This empowers retailers to take proactive steps to enhance customer satisfaction and loyalty. 

3. Finance Industry: 

Generative AI in Banking: Generative AI can streamline loan application processes by automatically generating personalized loan offers and risk assessments. This reduces processing time and improves customer service efficiency. 

4. Technology Industry: 

Generative AI for Software Testing: Imagine automating the creation of large-scale test datasets for various software functionalities. Generative AI can expedite the testing process, identify potential vulnerabilities more effectively, and contribute to faster software releases. 

Generative AI for Hi-Tech: This technology can accelerate innovation in various high-tech fields by creating novel designs for microchips, materials, or even generating code snippets to enhance existing software functionalities. 

Generative AI for Telecom: Generative AI can optimize network performance by predicting potential obstruction and generating data patterns to simulate network traffic scenarios. This allows telecom companies to proactively maintain and improve network efficiency. 

5. Generative AI Beyond Industries: 

GenAI Powered Search Engine: Imagine a search engine that understands context and intent, generating relevant and personalized results tailored to your specific needs. This eliminates the need to sift through mountains of irrelevant information, enhancing the overall search experience. 

Product Engineering with Generative AI: Design teams can leverage generative AI to create new product prototypes, explore innovative design possibilities, and accelerate the product development cycle. 

Machine Learning with Generative AI: Generative AI can be used to create synthetic training data for machine learning models, leading to improved accuracy and enhanced efficiency. 

Global Data Studio with Generative AI: Imagine generating realistic and anonymized datasets for data analysis purposes. This empowers researchers, businesses, and organizations to unlock insights from data while preserving privacy. 

6. Learning & Development with Generative AI: 

L&D Shares with Generative AI: This technology can create realistic simulations and personalized training modules tailored to individual learning styles and skill gaps. Generative AI can personalize the learning experience, fostering deeper engagement and knowledge retention. 

HFS Generative AI: Generative AI can be used to personalize learning experiences for employees in the human resources and financial services sector. This technology can create tailored training programs for onboarding, compliance training, and skill development. 

7. Generative AI for AIOps: 

AIOps (Artificial Intelligence for IT Operations) utilizes AI to automate and optimize IT infrastructure management. Generative AI can further enhance this process by predicting potential IT issues before they occur, generating synthetic data for simulating scenarios, and optimizing remediation strategies. 

Conclusion: 

The potential of generative AI is vast, with its applications continuously expanding across industries. As research and development progress, we can expect even more groundbreaking advancements that will reshape the way we live, work, and interact with technology. 

Reference- https://articlescad.com/the-generative-ai-revolution-transforming-industries-with-brillio-231268.html 

[deepdreamnights]

A British telecom company has made a generative AI bot that takes calls from scammers while impersonating a baffled old grandmother that tells meandering stories and goes on weird tangents to waste the scammers' time while also recording everything to get information on their operations.

This is, in a word, awesome.

[priyanshusoni]

7 Ways to Promote Responsible Use of Generative AI

Responsible Use of Generative AI Introduction As the field of artificial intelligence continues to evolve, one aspect that has garnered significant attention is generative AI. This technology, often referred to as deep learning or neural networks, has the ability to create new and original content based on patterns and data it has been trained on. While the applications of generative AI are…

[mariacallous]

On Tuesday, New Hampshire attorney general John Formella said that a Texas-based telecom company was behind the reportedly AI-generated robocalls impersonating President Joe Biden that went out ahead of the state’s presidential primary last month.

At a press conference on Tuesday, Formella announced that he had identified Life Corporation and its owner, Walter Monk, as the source behind the thousands of calls and that his office issued a cease-and-desist letter to the company and had opened a criminal investigation into the matter. The Federal Communications Commission sent its own cease-and-desist letters to Life Corporation, as well as another Texas company, Lingo Telecom, the alleged voice service provider of the calls.

“Ensuring public confidence in the electoral process is vital,” Formella said at the Tuesday press conference. “We're providing this update and information today to assure the public that we take this seriously and that this is one of our most important priorities. We are also providing this update and information to send a strong message of deterrence to any person or entity who would attempt to undermine our elections through AI or other means.”

Formella said that anywhere from 5,000 to 25,000 of these robocalls were placed ahead of the New Hampshire primary that mimicked Biden and discouraged voters from voting. “Your vote makes a difference in November, not this Tuesday,” the robocall said.

In January, WIRED reported that two teams of researchers had determined that the call was created with voice-cloning software from the AI startup Eleven Labs. The company declined to take responsibility for the Biden clone, telling WIRED that it was “dedicated to preventing the misuse of audio AI tools.”

Last week, the FCC put out a new proposal to ban robocalls that use AI-generated voices by updating the Telephone Consumer Protection Act, a 1991 law that regulates telemarketers. The FCC has used the TCPA in the past to go after junk callers, including conservative activists Jacob Wohl and Jack Burkman. In 2021, the FCC fined the pair more than $5 million for violating the law after they placed calls threatening to release the personal information of voters if they voted by mail in the 2020 election.

“Consumers deserve to know that the person on the other end of the line is exactly who they claim to be,” FCC chairwoman Jessica Rosenworcel said in a statement on Tuesday.

[partisan-by-default]

Mobile operator O2 has created an AI-powered tool that sounds like an elderly grandmother, keeping phone scammers on calls and away from the general public. The telecoms giant said it had created the so-called “scambaiter” tool in response to research which found that seven in 10 people wanted to get their own back on scammers but did not want to waste their own time in doing so.

The firm said it had worked with leading scambaiters – people who take on and disrupt scammer networks – to get phone numbers linked to its AI tool, known as Daisy, added to known lists used by scammers to target vulnerable consumers, and had been given the voice of an elderly grandmother to play on scammer biases about older people.

It said the tool had been successful in keeping numerous scammers on calls for up to 40 minutes at a time and frustrated them with meandering stories and explanations about their tech use, as well as providing false personal information and made-up bank details.

O2 said that by tricking fraudsters into thinking they were scamming a real person, Daisy has prevented them from targeting real victims, but had also exposed the common tactics used so the firm can help customers better protect themselves.

[news365timesindia]

[ad_1] Reliance Jio Infocomm chairman Akash M Ambani | Image: PTI3 min read Last Updated : Oct 15 2024 | 12:41 PM IST Speaking at the inauguration of the India Mobile Congress on Tuesday, the leaders of Reliance Jio and Bharti Airtel called for the government to embrace a holistic artificial intelligence (AI) strategy and ensure all potential satellite communication providers are subject to the same rules as traditional telecom operators. Reliance Jio Infocomm chairman Akash M Ambani and Bharti Enterprises chairman Sunil Bharti Mittal outlined their suggestions for the evolving sector in their address to a major gathering of national and global delegates from the telecom sector, including Prime Minister Narendra Modi and telecom minister Jyotiraditya Scindia. Click here to connect with us on WhatsApp  Market leader Reliance Jio wants the government to adopt a holistic AI strategy focused on self-sufficiency. "AI is absolutely critical for realising our dreams of a viksit Bharat by 2047. Therefore, India under your leadership should urgently embrace AI with a holistic strategy driven by maximum Atmanirbhar efforts," Ambani said. He stressed that Jio remains committed to democratising AI and offering powerful AI models and services to Indians at affordable prices. "Towards this end, we are laying the groundwork for a national AI infrastructure," he emphasised. Ambani noted that India needs to accelerate talent generation on a scale necessary to make the country a global leader in AI. Addressing the concern over how AI might affect the job market, he remarked that some existing jobs will evolve while many new and exciting opportunities for employment and entrepreneurship "will be created rapidly, just like during the adoption of the computer and the internet." Additionally, Ambani urged the government to expedite the draft of the 2020 data centre policy. "Indian data should remain in Indian data centres. Therefore, Indian companies ready to set up AI and machine learning data centres should receive all necessary incentives, including incentives for power consumption," he added. Satcom debate Bharti Airtel has called on the government to ensure that all potential satellite communication providers operate under the telecom operator framework. Drawing the Prime Minister's attention to the ongoing global debate on how fast-growing satellite communication services can coexist with terrestrial networks, Mittal highlighted that telecom companies worldwide have played a crucial role in connecting the globe. Referring to Indian telcos, he noted that they would extend satellite services to the remotest parts of the country. However, Mittal stressed that satellite companies aiming to serve "elite, retail customers" in urban areas must take a telecom licence like everyone else. His comments appear directed at foreign entities such as Starlink and Project Kuiper, which are seeking entry into the Indian market and whose applications are currently being reviewed by the government. "They must adhere to the same conditions, including buying spectrum like telecom companies, paying the licence fees, and securing their networks. This is a simple solution that can be adopted on a global scale, and India can lead the way," Mittal said. The government is currently in the process of opening up satellite communication services and has already granted GMPCS licences to Bharti Group-backed Eutelsat OneWeb and Reliance Jio’s satellite arm, Jio Space Limited. However, applications from foreign entities have faced hurdles due to technicalities and security concerns. Starlink is the satellite internet constellation operated by SpaceX, the American spacecraft manufacturer and satellite communications company owned by US tech billionaire Elon Musk. Project Kuiper, a subsidiary of Amazon, was established in 2019 to deploy a large satellite internet constellation to provide low-latency broadband connectivity. First Published: Oct 15 2024 | 12:41 PM IST

[aionlinemoney]

Reliance Industry launching Jio AI Cloud Welcome offer upto 100 GB Free Storage

Jio, a part of the Reliance Industry and a major telecom company in India, has been a main player in the change of the country’s digital transformation for the past many years. Jio is Known for its innovative digital services, Jio has significantly changed the market with a range of offerings in telecom services. The latest addition to its lineup is Jio AI Cloud, a modern cloud platform, aimed at businesses, developers, and individual users. In this article, we will discuss what Jio AI Cloud is, its offers, launch details, and how it benefits users by providing secure storage and easy access to digital content such as photos, videos, documents, and other data.

What is Jio AI cloud?

This is a cloud platform by Reliance industry that comes with built in artificial intelligence features to store your data secure and access it anywhere. It provides secure, and affordable cloud solutions for businesses and individuals, making it easy to store, manage, and analyze data. With this users can access powerful AI tools that enable smarter data management, better storage efficiency, and enhanced digital experiences. Whether for startups, large companies, or individual users, Jio AI Cloud offers reliable solutions for cloud storage with the added advantage of AI technology.

When will Jio AI cloud offer will launch :

Reliance industry is preparing for the launch Jio AI cloud  welcome offer and it is expected to be introduced in the market this Diwali. Reliance’s chairman Mukesh Ambani will launch Jio AI cloud with a welcome offer upto 100 GB free cloud storage for Jio users. The users are awaiting and excited for it. Also Reliance industry has introduced AI innovative technologies called Jio Brain and the Reliance industry is also planning to establish Giga byte scale ready AI data center in Jamnagar, Gujarat.

Benefits of Jio AI Cloud for Secure Storage and Access to Digital Content :

Jio Cloud provides free cloud storage and easily store and access your data, such as photos, videos, documents, and more.Here are some key benefits that make it a great choice:

Highly Secure Cloud Storage:

Jio AI Cloud organizes security by using advanced multi-layered security measures to protect user data from unauthorized access and cyber threats. With end-to-end encryption and strong authentication, users can trust that their photos, videos, documents, and other digital content are securely stored the data into their data centers. Reliance’s chairman Mukesh Ambani has told in the 47th annual general meeting of Reliance industry.

Backup and Real-time Syncing :

Jio AI Cloud offers automatic backups and real-time syncing of digital content across devices. This ensures that important photos, videos, documents, and other data are never lost, even if a device is lost or damaged. Real-time syncing ensures that any updates to a file on one device are immediately updated on all connected devices.

Enhanced Access and Sharing Options :

Jio AI Cloud allows users to access their digital content from any device, anywhere, as long as they have an internet connection. The platform also provides easy sharing options, enabling users to create secure links for sharing photos, videos, and documents. This makes it simple and convenient to collaborate with colleagues, friends, and family.

Cost Effective Storage plans :

Jio AI Cloud is likely to provide flexible pricing options, including a pay-as-you-go plan where users pay only for the resources they use. This is especially useful for individuals and businesses looking to control costs while enjoying advanced cloud services.

Conclusions :

Jio AI Cloud represents a major growth in cloud storage in India. Reliance is set to launch a Diwali offer of 100GB free cloud storage, this platform is expected to attract a diverse range of users, from individuals needing secure storage for personal data to businesses seeking scalable, AI-enhanced cloud solutions. With its advanced AI features, robust security, seamless integration with other Jio services, and competitive pricing, Jio AI Cloud is controlled to be a strong competitor in the cloud services industry. As Reliance industry continues to expand its digital innovations, the Jio AI Cloud could significantly change how digital content is stored, managed, and accessed in India.

[infinitemonkeytheory]

Voters in New Hampshire were treated in January to a call purporting to be from President Biden telling them not to vote in the primary. After a brief but intense investigation, the perpetrator has been revealed to be Life Corporation, a Texas-based company that has been caught slinging disinformation before.

[…]

Investigators traced the calls to a shady telecoms provider called Lingo, which has also gone by Americatel, BullsEyeComm, Clear Choice Communications, Excel Telecommunications, Impact Telecom, Matrix Business Technologies, Startec Global Communications, Trinsic Communications and VarTec Telecom. The FCC notes that the company (whatever its name really is) has been doing illegal call operations for years.

Lingo, however, was only doing the transmission of the calls on behalf of Life Corporation, a Texas company owned by one Walter Monk and also no stranger to illegal activity. The FCC notes that it cited Life and Monk in 2003 “for delivering apparently illegal prerecorded and unsolicited advertisements to residential lines.”

[kenresearchreport]

Decoding Cybersecurity: Unveiling the Future of US Digital Forensics Excellence

What is the Size of US Digital forensics Industry?

US Digital forensics Market is expected to grow at a CAGR of ~% between 2022-2028 and is expected to reach ~USD Mn by 2028.

Escalating cyberattacks targeting individuals, organizations, and critical infrastructure underscore the need for robust digital forensics capabilities. The increasing frequency and sophistication of these attacks drive the demand for advanced tools and expertise to investigate and respond effectively.

Rapid technological advancements, including IoT, cloud computing, AI, and blockchain, introduce new avenues for cyber threats. Digital forensics services are crucial to understanding these emerging technologies' vulnerabilities and mitigating associated risks.

Furthermore, stricter data protection regulations and compliance mandates necessitate thorough digital evidence collection, preservation, and analysis.

Organizations across industries has invested in digital forensics to ensure adherence to legal requirements and regulatory frameworks.

Additionally Legal proceedings increasingly rely on digital evidence. Law enforcement, legal firms, and corporations require robust digital forensics services to gather, analyze, and present evidence in a court of law, driving market expansion.

Us Digital Forensics Market By Type

The US Digital forensics market is segmented by Computer Forensics, Network Forensics, Mobile Device forensics and Cloud forensics. Based on type, Computer Forensics type segment is emerged as the dominant segment in US Digital forensics market in 2022.

Computers are ubiquitous in modern society, utilized across industries, organizations, and households. As a result, a significant portion of digital evidence related to cybercrimes and incidents is generated from computer systems, driving the demand for specialized computer forensics expertise. Computers and their software environments evolve rapidly.

Us Digital Forensics Market By End User Application

US Digital forensics market is segmented by Government and Defence, BFSI, Telecom and IT, Retail, Healthcare and Other Government and Defence market is dominant in end user application segment in Digital forensics market in 2022.

Government and defense agencies handle highly sensitive information related to national security and intelligence. The increasing sophistication of cyber threats targeting these entities necessitates robust digital forensics capabilities to investigate and respond to cyber incidents effectively.

Government and defense entities are prime targets for cyberattacks due to their critical roles. Effective incident response through digital forensics helps in containing and mitigating cyber incidents swiftly, minimizing damage and preventing further breaches.

US Digital forensics by Region

The US Digital forensics market is segmented by Region into North, East, West, South.  In 2022, the dominance region is East region in US Digital forensics market.

The East region has a dense population and a well-established digital infrastructure, making it a hotspot for cybercriminal activity. The higher frequency of cyber threats and incidents necessitates a strong emphasis on digital forensics to investigate and mitigate these risks effectively. Additionally, the East region often sees a proactive approach from regulatory and legal bodies, reinforcing the demand for digital forensics services to ensure compliance and assist in investigations. The proximity of key players in law enforcement, government agencies, legal firms, and corporate headquarters further fuels the need for robust digital forensics capabilities.

Download a Sample Report of US digital forensics Solution Market

Competition Scenario in US Digital forensics Market

The US digital forensics market is characterized by a competitive landscape with several key players competing for market share. Prominent companies offering a range of digital forensics solutions and services contribute to the market's dynamism.

The competitive landscape also includes smaller, specialized firms and start-ups that focus on niche areas of digital forensics, such as cloud forensics, memory forensics, and industrial control systems forensics.

The competition is further intensified by the continuous evolution of technology, leading to the emergence of new players and innovative solutions. As the demand for digital forensics continues to grow, companies in this market are likely to invest in research and development to stay ahead of the curve, leading to a consistently competitive environment.

What is the Expected Future Outlook for the Overall US Digital forensics Market?

Download a Custom Report of US digital forensics market Growth

The US Digital forensics market was valued at USD ~Million in 2022 and is anticipated to reach USD ~ Million by the end of 2028, witnessing a CAGR of ~% during the forecast period 2022- 2028.

The US digital forensics market is poised for robust expansion due to the ever-evolving cybersecurity landscape, technological advancements, and regulatory pressures. Organizations across industries will increasingly recognize the necessity of investing in digital forensics to safeguard their digital assets and ensure compliance.

 As long as cyber threats continue to evolve, the demand for sophisticated digital forensic tools, services, and expertise will remain on an upward trajectory.

The US digital forensics market appears promising, characterized by a confluence of technological advancements, increasing cyber threats, and growing legal and regulatory requirements. As technology continues to evolve rapidly, so does the nature of cybercrimes, creating a persistent demand for digital forensics solutions and services.

Additionally, the escalating frequency and complexity of cyberattacks. As more critical operations and personal information are digitized, the potential attack surface expands, leading to a higher likelihood of security breaches. This dynamic compels organizations and law enforcement agencies to enhance their digital forensic capabilities to investigate, mitigate, and prevent cyber incidents effectively.

Furthermore, the rise of emerging technologies like the Internet of Things (IoT), artificial intelligence (AI), and blockchain presents both opportunities and challenges. These technologies bring new possibilities for efficiency and connectivity but also introduce novel avenues for cyber threats. Consequently, the demand for digital forensics services is expected to surge as organizations seek expertise in unraveling incidents involving these cutting-edge technologies.

The market is also likely to see increased adoption of cloud-based digital forensics solutions. As more data is stored and processed in the cloud, digital forensic providers will need to develop tools and methodologies to effectively gather evidence from virtual environments, remote servers, and distributed systems.

[arcobalengo]

Muore oggi Roberto Colaninno, il più importante "capitano coraggioso" dei ruggenti anni novanta. Quando si affacciò una nuova classe imprenditoriale che oggi non esiteremmo a chiamare di "robben barons" per dirla all'americana: baroni ladri, speculatori, spoliatori del patrimonio pubblico.

Patrimonio Pubblico svenduto per un piatto di lenticchie da quelli che allora ineguamente consideravamo la crema dei civil servant dello stato italiano: Carlo Azeglio Ciampi, Romano Prodi e Massimo D'Alema.

Colaninno, guidò una cordata di imprenditori all'assalto della Telecom Italia, società leader ad alta redditività, senza debiti: la migliore Tlc company europea sicuramente. La acquistatono attraverso un "veicolo" (così le chiamavano all'ora) società con capitale irrisorio, la Tecnimont; troppo se questa società aveva una linea telefonica e una segretaria. Fatto sta che con i soldi a prestito di un pool di banche guidate da Mediobanche riuscì nell'impresa dell'acquisto. L'inghippò si capì dopo; Colaninno fuse la Tecnimont carica di debiti nella TIM società gioiello della Telecom Italia. In parole semplici con la fusione il risultato era che la TIM pagava l'acquisto della società madre Telecom Italia alla società acquirente e superindebitata Tecnimont. Loro assieme ai giornali compiacenti chiamarono l'operazione Leverage buyout: gli allocchi come ero io ci credettero al volo. Il Financial Times in una Lex Column dell'epoca definì l'operazione per quello che era, letteralmente "Una rapina in pieno giorno". La Telecom da quel giorno era una società zombificata. Tutte cose avvenuto sotto il buon governo ciampian prodian d'alemiano. La Crema. Il Meglio.

Se Berlusconi avesse fatto una operazione del genere, il pool di Milano avrebbe mandato una divisione corazzata a prenderlo. Non aggiungo altro. Se non quello di constatare quanto potevo essere stupido io a credere ad una simile masnada di banditi politici.

Poi arrivò Tronchetti Proverà che rilevò da Colaninno e amici che così uscirono dalla storia carichi di banconote senza aver mai rischiato nulla. La Rapina del Secolo.

A conclusione aggiungo che Colaninno ci ha fatto anche lo sfregio di candidare il figlio scemo (o troppo signore, tanto il lavoro sporco l'ha fatto il padre) nel PD mettendecelo a carico - da parlamentare - per una ventina d'anni. E noi, idioti, lo abbiamo votato.

Un capolavoro, Chapeau Ragionier Colaninno.

Giuseppe Masala

[abigailnussbaum]

I've been noticing this too, and it feels like the most insidious tool in the AI industry's efforts to convince us that their product - which is prohibitively expensive, legally dubious, and objectively does not work - is "inevitable". It probably helps that it really does seem to be an organic phenomenon - non-AI tech company CEOs, having been incepted into the idea that this technology is the future, are rushing to slap it on their products for fear of being left behind. So, inasmuch as "AI" as it's being used today has a concrete meaning - a large language model used for text or image generation in response to natural language queries - it's now being applied to any kind of algorithmic tool, whether preexisting or new, in the misguided belief that this makes it sound more sophisticated.

For an example that I've witnessed close-hand, my company's VP of R&D recently announced, in an all-hands state of the company talk, that we were looking into incorporating AI into our product. Which raised a lot of eyebrows among us engineers, since our products are high speed network routers that we sell to telecoms and other internet service providers. Not only do they have no use for text or image generation, you can't assume that they'd have access to a service like ChatGPT (just because a device passes network traffic doesn't mean it has access to the open internet; your home wifi router doesn't necessarily have the ability to surf the web). Not to mention that our customers might have a problem with us passing their customer data to a third-party server. And since these are all firmware-based devices, we don't have the spare memory or computing capabilities to run our own LLM engine on each device.

Turns out he was talking about some kind of fancy algorithm to evaluate network load and adjust capacity dynamically. Currently we offer fairly sophisticated tools that allow customers to designate specific bandwidth channels for each of their customers, and prioritize different types of traffic (for example, if you're a telecom, voice traffic is always prioritized over data traffic, because a dropped packet in voice registers in a way that a dropped data packet doesn't). But this all has to be configured ahead of time, and the idea with this new tool is to be able to analyze the traffic in real time and respond to it without operator input. It sounds really neat, and I wouldn't be surprised if there's a machine learning component to it, but it's not what AI as the term is currently being used actually means. It's honestly a bit sad to me that if we actually get this kind of genuinely exciting, innovative tool off the ground, we'll have to slap the name of an environmentally wasteful plagiarism engine on it to get customers interested.

(There's also been some talk about using AI in coding. Apparently there's a team working on tools for that, though they haven't presented them to us yet. Personally, I'm dubious. Most of my work involves plugging into preexisting code, some of it decades old. It requires understanding systems, and the coding part is actually the smallest aspect of it. And yes, when I've developed features from scratch, there's a degree of repetition that a text generator might be able to help with - but as it happens, I already have tools that do some of that work, generating, for example, the code for new user commands from a definition document. But those tools are called compilers - the actual definition of "compiler" is any program that translates from one machine language to another - and I don't see how an AI tool to do similar work would save me that much time.)

Latest tech pet peeve is the use of the term "AI" to refer to basically anything that does any amount of automation or uses computers in any way

[delvens1]

Smart Thermostat Market is Projected to Grow Massively in Near Future by 2030

Smart Thermostat MarketReport 2025 by Delvens offers comprehensive market insights, empowering businesses with a competitive edge. It includes detailed estimates for numerous segments and sub-segments, providing valuable strategic guidance, Smart Thermostat Market size is projected to reach USD 6.5 billion by 2026 at a CAGR of 21% from USD 2.6 billion in 2021 during the forecast to 2030.

Get Free Sample Report: https://www.delvens.com/get-free-sample/smart-thermostat-market

A thermostat is a device primarily used for the purpose of maintaining a particular temperature in a closed room. These are equipped with relays, switches and valves in order to generate signals for the temperature modulation. A smart thermostat is AI driven and perform the same function but use Wi-Fi for the purpose.

With the recent trend of smart home and smart home voice gaining popularity along with the governmental regulations are some of the factors that have supported long-term expansion for Smart Thermostat Market.

Regional Analysis

APAC is expected to be the largest market during the forecast period. With the growing popularity along with the environmental awareness has led to the expansion of market in the region.

Top Key Players:

Alphabet

Emerson Electric

Honeywell International

Lennox International

Ecobee

Carrier Corporation

Johnson Controls

Legrand (Netatmo)

Resideo Technologies

Siemens

Trane Technologies

MRCOOL

Radio Thermostat Company of America

Salus Controls

Vine Connected

VIvint

Zen Ecosystems and More

Recent Developments: Smart Thermostat Market

Carrier came up with an updated zoning sensor which could be used with its flagship Infinity System.

Google Nest came up with an all new version of Nest Thermostat by bringing AI in the play.

Smart Thermostat Market is segmented into Products, Connectivity Technology, Installation Type, Vertical and geography.

On the basis of Products

Connected Smart thermostat

Learning Smart Thermostat

Standalone Smart Thermostat

On the basis of Connectivity Technology

Wireless Network

Wired Network

On the basis of Installation Type

New Installation

Retrofit Installation

On the basis of Vertical

Residential

Commercial

On the basis of Region

Asia Pacific

North America

Europe

South America

Middle East & Africa

Access Full Report: https://www.delvens.com/report/smart-thermostat-market

In addition to the market data for Smart Thermostat Market, Delvens offers client-centric report and customized according to the company’s specific demand and requirement.

More Related Reports:

Smart Home Appliances Market

Smart Bed Market

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Delvens is a strategic advisory and consulting company headquartered in New Delhi, India. The company holds expertise in providing syndicated research reports, customized research reports and consulting services. Delvens qualitative and quantitative data is highly utilized by each level from niche to major markets, serving more than 1K prominent companies by assuring to provide the information on country, regional and global business environment. We have a database for more than 45 industries in more than 115+ major countries globally.

Delvens database assists the clients by providing in-depth information in crucial business decisions. Delvens offers significant facts and figures across various industries namely Healthcare, IT & Telecom, Chemicals & Materials, Semiconductor & Electronics, Energy, Pharmaceutical, Consumer Goods & Services, Food & Beverages. Our company provides an exhaustive and comprehensive understanding of the business environment.

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[rainyducktiger]

Software-defined Anything Market Future Demand and Evolving Business Strategies to 2033

The rise of cloud computing, virtualization, and AI-driven automation has ushered in a new era of data center and infrastructure management — one defined not by hardware, but by software. This evolution is embodied in the growing global market for Software-defined Anything (SDx), a collective term for software-driven solutions that decouple hardware functionality from the physical layer and enable unprecedented flexibility, scalability, and efficiency across IT environments.

As digital transformation becomes a central strategic goal for organizations worldwide, SDx is expected to be one of the most transformative trends shaping the future of computing and network architecture over the next decade.

Market Overview

The Software-defined Anything (SDx) market refers to technologies that replace hardware-defined infrastructure functions (such as storage, networking, and data center management) with software-based solutions, creating programmable, agile, and automated IT environments.

From software-defined networking (SDN) to software-defined storage (SDS), and even software-defined data centers (SDDC), SDx solutions empower organizations to dynamically adapt and optimize their IT infrastructure based on business needs rather than hardware limitations.

In 2023, the global SDx market was valued at approximately USD 62 billion, and it is projected to grow at a robust CAGR of 23.5%, reaching over USD 265 billion by 2032. This remarkable growth is being driven by rising demand for flexible IT frameworks, increasing cloud adoption, and the explosive growth in data generation from Internet of Things (IoT) devices, 5G networks, and artificial intelligence applications.

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Key Drivers of Market Growth

1. Demand for IT Agility and Flexibility

Traditional hardware-based infrastructures often struggle to keep up with the rapid pace of digital business. Enterprises increasingly require agile, adaptable systems that can be provisioned, scaled, and optimized on the fly.

SDx solutions enable:

Reduced hardware dependency.

Dynamic resource allocation.

Automated policy-based management.

Seamless cloud-native integration.

This agility is invaluable for companies undergoing cloud migration, digital transformation, or global expansion.

2. Data Center Modernization

As businesses increasingly shift workloads to hybrid and multi-cloud environments, the need for software-defined data centers (SDDC) has become urgent. SDDCs allow organizations to virtualize and manage compute, storage, and networking resources from a centralized, software-based control plane.

This trend is particularly prominent in:

Banking and financial services (BFSI).

Healthcare IT.

Retail and eCommerce.

Manufacturing industries deploying Industry 4.0 technologies.

3. 5G Rollout and Edge Computing

The advent of 5G networks and edge computing creates a new set of demands for real-time data handling, traffic routing, and software-defined resource management. Telecom providers and enterprises alike are investing in SDN and Network Function Virtualization (NFV) to improve scalability and reliability at the network edge.

4. Cost Optimization

SDx minimizes the reliance on proprietary, vendor-locked hardware, leading to substantial cost savings for enterprises. By using commodity hardware and overlaying it with intelligent software systems, organizations can:

Reduce capital expenditure (CapEx).

Minimize operational expenditure (OpEx) via automation.

Streamline IT maintenance and upgrades.

Challenges in the Market

While SDx promises many benefits, the road to adoption is not without obstacles:

Security Concerns: Virtualizing hardware functions can create complex attack surfaces if security is not built into the software layer.

Integration Issues: Migrating from legacy hardware to SDx platforms often requires substantial re-engineering of existing systems.

Skill Shortage: A lack of experienced personnel trained in SDN, SDS, and cloud-native architectures remains a major adoption hurdle.

Market Segmentation

By Component

Software: Controllers, hypervisors, and management platforms.

Services: Consulting, implementation, training, and maintenance.

By Type

Software-defined Networking (SDN)

Software-defined Storage (SDS)

Software-defined Data Center (SDDC)

Software-defined Security (SDSec)

Software-defined Wide Area Network (SD-WAN)

Each category is expected to see robust growth, with SD-WAN and SDDC solutions leading the charge due to enterprise cloud adoption.

By End-user

IT and Telecom

BFSI

Retail and eCommerce

Manufacturing

Healthcare

Government and Public Sector

Telecom and IT will dominate the market share due to 5G deployment and network virtualization, but healthcare and manufacturing are catching up as they digitize core processes.

Regional Insights

North America

North America leads the SDx market, thanks to early adoption of cloud services, strong demand for data center modernization, and the presence of key technology providers. The U.S. market is particularly robust, driven by its advanced tech ecosystem and heavy investment in AI and edge computing.

Europe

European enterprises are actively transitioning toward hybrid cloud and software-defined infrastructure to meet evolving data privacy and security regulations (such as GDPR). Germany, the UK, and France are the leading markets.

Asia-Pacific

The Asia-Pacific region is the fastest-growing SDx market. Rapid digitalization, growing mobile connectivity, and government-backed cloud initiatives in China, India, Japan, and Southeast Asia are accelerating market growth.

Industry Trends

1. AI-powered Infrastructure Automation

AI is playing a growing role in SDx by enhancing predictive maintenance, self-healing systems, anomaly detection, and policy-based automation. AI-powered SDx systems reduce downtime and improve resource utilization.

2. Hybrid Cloud and Multi-Cloud Strategies

As enterprises distribute workloads across private clouds, public clouds, and on-premises data centers, software-defined frameworks allow centralized control, seamless orchestration, and dynamic resource scaling.

3. Zero Trust Security Models

Software-defined security systems are enabling Zero Trust Architecture (ZTA), where all users, devices, and services must continuously authenticate, regardless of their network location. This is becoming standard practice as cybersecurity threats grow in complexity.

4. Containerization and Kubernetes Integration

Software-defined infrastructure increasingly integrates with container orchestration platforms like Kubernetes, allowing developers to deploy and manage applications more efficiently, particularly in microservices-driven environments.

Competitive Landscape

The Software-defined Anything market is highly competitive, characterized by a mix of established tech giants and innovative startups.

Leading companies include:

VMware, Inc.

Cisco Systems

Hewlett Packard Enterprise (HPE)

IBM Corporation

Dell Technologies

Arista Networks

Nutanix

Citrix Systems

Huawei Technologies

Strategic alliances, mergers, and acquisitions are common as companies race to expand their software-defined portfolios and strengthen their hybrid and multi-cloud capabilities.

Future Outlook

The Software-defined Anything market is set to be one of the cornerstones of enterprise IT over the next decade. As businesses demand more automation, flexibility, and resilience, software-defined solutions will replace rigid, hardware-bound systems.

Forecast Highlights:

By 2032, software-defined solutions will underpin over 70% of global enterprise IT infrastructure.

AI and machine learning will drive intelligent orchestration and predictive optimization across SDx platforms.

Industries like healthcare, retail, and manufacturing will rapidly close the gap with telecom and BFSI in terms of adoption.

Open-source SDx frameworks and API-driven ecosystems will foster innovation and reduce vendor lock-in.

Conclusion

The Software-defined Anything (SDx) market represents a seismic shift in how businesses architect and manage their IT environments. By decoupling hardware from software and enabling centralized, automated control of distributed resources, SDx solutions are redefining the future of digital infrastructure.

In an era of rapid digital transformation, software-defined technologies empower organizations to stay agile, reduce costs, and meet rising customer expectations, setting the stage for exponential market growth through 2032 and beyond.

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[mariacallous]

“King of Toxic Masculinity” Gets Hacked

Hacktivists have breached an online “educational platform” founded by the misogynistic right-wing influencer Andrew Tate reportedly revealing the email addresses of hundreds of thousands of users as well as the contents of the platforms’ private chat servers. Data from the hack, first reported by the Daily Dot, has now been published by the transparency nonprofit Distributed Denial of Secrets.

Andrew Tate, the so-called “king of toxic masculinity,” is currently under house arrest in Romania and faces two separate criminal charges, including allegations of forming an organized criminal group and trafficking women across Romania, the UK, and the US.

The compromised platform, a subscription-based service known as The Real World (formerly called Hustler's University), describes itself as a “global community” focused on “personal growth.” According to its website, members receive expert training, mentorship, and access to a wide range of educational courses for around $50 per month.

According to the Daily Dot, hacktivists announced their breach of the platform on Thursday by disrupting the course's main chatroom with a barrage of uploaded emojis while Tate was livestreaming an episode of his show Emergency Meeting on Rumble. The emojis included a transgender pride flag, a feminist fist, an AI-generated image of Tate wrapped in a rainbow flag.

Data from the breach, verified by WIRED, includes more than 700,000 usernames and reportedly includes messages from 221 public and 395 private chat servers. An analysis by the Daily Dot reveals a mix of content within the chat logs, ranging from motivational quotes and personal progress updates to grievances about the “LGBTQ agenda.” WIRED is continuing to analyze the leaked material.

[informationcommunicationtechnolo]

Reconciliation Software Market Innovation and Technology Impact

The Reconciliation Software Market size was USD 1.72 Billion in 2023 and is expected to grow to USD 6.49 Bn by 2032 and grow at a CAGR of 15.9% by 2024-2032.

The Reconciliation Software Market is rapidly gaining prominence as financial institutions, fintech companies, and large enterprises strive for greater accuracy, transparency, and automation in financial reporting. As digital transactions become more complex and voluminous, reconciliation software is emerging as a critical tool to streamline and verify financial data, detect discrepancies, and ensure regulatory compliance.

The Reconciliation Software Market are being integrated into broader financial systems to create a seamless, end-to-end financial workflow—reducing operational risk and increasing productivity.

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Market Keyplayers:

ReconArt Inc.

Oracle Corporation

BlackLine Inc.

Broadridge Financial Solutions, Inc.

SolveXia

Tata Consultancy Services Limited

Xero Limited

SmartStream Technologies Ltd

The global Reconciliation Software Market has witnessed significant growth due to increasing demand for financial automation, tighter regulatory requirements, and a rising need for real-time financial visibility. Organizations are moving away from spreadsheets and legacy systems toward AI-enabled, cloud-based reconciliation solutions that support high-speed, accurate processing of large transaction volumes.

According to market intelligence reports, the market size is estimated to surpass USD 1.6 billion in 2024 and is projected to reach over USD 3.2 billion by 2030, registering a CAGR of approximately 12% during the forecast period. Major players in this space include FIS, Oracle, BlackLine, Trintech, Broadridge, and AutoRek, all investing in AI and cloud technologies to enhance software capabilities.

Scope and Applications

The scope of reconciliation software extends across multiple domains—bank reconciliation, intercompany reconciliation, payment reconciliation, and securities reconciliation. These solutions automate the matching of internal records with external data from banks, vendors, and third-party systems, helping organizations detect discrepancies swiftly and accurately.

Applications span across industries: in banking, it’s used for high-frequency transaction validation; in retail, it ensures POS transaction accuracy; and in insurance and telecom, it aids in premium and billing reconciliation. With increasing regulatory oversight, particularly in financial services, reconciliation software also serves as a compliance enabler by generating audit trails and standardized reports.

Market Forecast

Looking forward, the reconciliation software market is poised for consistent growth, bolstered by increasing digitization in financial operations and a growing focus on operational resilience. Cloud-based solutions will dominate due to their scalability, flexibility, and cost-efficiency. Small and medium-sized enterprises (SMEs) are expected to contribute significantly to this growth as cloud offerings become more accessible and affordable.

North America remains the largest market due to early adoption and advanced financial infrastructure, while Asia-Pacific is expected to register the fastest growth rate due to rapid digital adoption, fintech expansion, and increased cross-border transactions.

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Market Segmentation:

By Deployment:

Cloud

On-premise

By Component:

Software

Services

By Enterprise Size:

Small and Medium-sized Enterprises

Large Enterprises

By End-use:

Financial Institutions

Banks

Insurance

Key Trends

Several notable trends are shaping the reconciliation software landscape:

AI and Machine Learning Integration: These technologies are enhancing anomaly detection and predictive reconciliation.

Cloud-First Architecture: Organizations are favoring SaaS models for ease of deployment and reduced infrastructure costs.

Regulatory Tech (RegTech) Synergy: Reconciliation platforms are being integrated with RegTech tools to streamline compliance processes.

Real-time Reconciliation: Increasing demand for instant financial insights is pushing vendors toward real-time processing solutions.

API-led Integrations: Open banking and interconnected systems are driving demand for reconciliation tools that support seamless integration with ERPs, CRMs, and banking platforms.

Future Prospects

The future of the reconciliation software market looks promising with significant innovations on the horizon. Emerging technologies such as blockchain may offer immutable records for transaction verification, further enhancing the integrity of reconciliation processes. Automation will continue to reduce manual intervention, allowing finance teams to focus on exception handling and strategic tasks.

Moreover, with increasing adoption of embedded finance and buy-now-pay-later (BNPL) models, the complexity of transaction ecosystems is increasing, creating a greater need for robust reconciliation mechanisms. Vendors that offer modular, AI-driven, and industry-specific solutions are likely to gain a competitive edge.

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Conclusion

In conclusion, the Reconciliation Software Market is experiencing a strong surge as businesses seek to modernize and secure their financial operations. With growing volumes of digital transactions and stricter regulatory environments, reconciliation solutions are no longer optional—they are strategic necessities.

As automation, AI, and cloud computing continue to redefine financial processes, reconciliation software will play a pivotal role in ensuring data accuracy, operational efficiency, and compliance. The market’s growth trajectory reflects a future where real-time, intelligent reconciliation becomes standard across industries, paving the way for smarter financial management and greater transparency.

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