#Retail Media Network Market Analysis

[yashvicmi01]

Global Retail Media Network Market Is Estimated To Witness High Growth Owing To the Rising Trend of Online Shopping

The global Retail Media Network Market is estimated to be valued at USD 18.82 Bn in 2022 and is expected to exhibit a CAGR of 6.39% over the forecast period 2023-2029, as highlighted in a new report published by Coherent Market Insights.

A) Market Overview:

The Retail Media Network Market refers to the advertising services provided by retailers to brands on their digital platforms, such as websites and mobile apps. These networks enable brands to reach a large and targeted audience by placing advertisements in strategic locations within the retailer's digital ecosystem. This market offers various advantages, such as increased brand visibility, higher customer engagement, and measurable return on investment. With the growing trend of online shopping, retailers are leveraging their digital platforms to monetize their online presence through advertising, thus fueling the growth of the Retail Media Network Market.

B) Market Key Trends:

One key trend driving the growth of the Retail Media Network Market is the increasing adoption of programmatic advertising. Programmatic advertising allows brands to automate the process of buying and selling ad space, making it more efficient and cost-effective. With the help of algorithms and real-time bidding, brands can target their advertisements to specific audience segments, resulting in higher engagement and conversion rates. For example, Walmart's advertising platform, Walmart Media Group, uses programmatic advertising to deliver personalized ads to its customers based on their purchase history and online behavior.

C) Porter's Analysis:

- Threat of new entrants: The Retail Media Network Market is highly competitive, with established players already dominating the market. New entrants would face challenges in building strong relationships with retailers and brands, as well as competing against the existing networks.

- Bargaining power of buyers: Brands have a certain level of bargaining power as they can choose between multiple retail media networks to advertise their products. However, the effectiveness and reach of the network play a crucial role in their decision-making process.

- Bargaining power of suppliers: Retailers, as the suppliers of advertising space, hold the bargaining power in the market. They can negotiate favorable terms and pricing with the brands and exert control over the placement and visibility of advertisements.

- Threat of new substitutes: While there may be alternative advertising channels available, such as traditional media or social media platforms, the targeted and interactive nature of retail media networks provides unique advantages for brands.

- Competitive rivalry: The Retail Media Network Market is characterized by intense competition among key players, such as Walmart, Amazon, and Target. These players continuously strive to innovate and improve their offerings to attract brands and capture a larger share of the market.

D) Key Takeaways:

1. The global Retail Media Network Market is expected to witness high growth, exhibiting a CAGR of 6.39% over the forecast period. This growth is driven by the increasing trend of online shopping, which has led retailers to leverage their digital platforms for advertising.

2. In terms of regional analysis, North America is expected to dominate the market due to the presence of major retail players, such as Walmart, Amazon, and Costco. However, Asia Pacific is expected to be the fastest-growing region, fueled by the rising adoption of e-commerce and digital advertising in countries like China and India.

3. Key players operating in the global Retail Media Network Market include Walmart, Costco Wholesale Corporation, The Kroger Co., Walgreens Boots Alliance, Inc., TESCO PLC, Amazon.com, Inc., METRO, Home Depot Product Authority, LLC., Target Brands, Inc., Best Buy, Inter IKEA Systems B.V, Carrefour SA, and eBay Inc. These players are investing in advanced technologies and strategic partnerships to enhance their advertising platforms and maintain a competitive edge in the market.

In conclusion, the Retail Media Network Market is poised for significant growth, driven by the increasing trend of online shopping and the adoption of programmatic advertising. Retailers and brands are leveraging these networks to enhance their reach, visibility, and customer engagement, creating lucrative opportunities in this evolving market.

[writerblogs]

Global Retail Media Networks Market Is Estimated To Witness High Growth Owing To Increasing Digital Advertising Expenditure & Rapid Growth of E-commerce

The global Retail Media Networks Market is estimated to be valued at US$ 1,227.84 million in 2021 and is expected to exhibit a CAGR of 19.03% over the forecast period of 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.

A) Market Overview:

Retail media networks are a digital advertising platform that enables retailers to monetize their digital real estate. These networks allow brands to promote their products and services directly to consumers while they are engaged in the online shopping experience. With the rapid growth of e-commerce and the increasing digital advertising expenditure, retail media networks have emerged as an effective marketing channel for retailers and brands.

B) Market Dynamics:

1. Increasing Digital Advertising Expenditure: With the shift towards digital advertising, brands are investing more in online advertising platforms to reach a wider audience. Retail media networks provide a targeted and measurable advertising solution, resulting in increased brand awareness, customer engagement, and sales.

2. Rapid Growth of E-commerce: The rise in e-commerce has transformed the retail landscape, offering opportunities for retailers to connect with customers online. Retail media networks enable retailers to leverage their online platforms and data to deliver personalized and relevant advertising messages to shoppers, ultimately driving conversions and sales.

C) Segment Analysis:

In terms of the segment analysis, the market can be segmented based on platform type, format, and end-use industry. One dominant segment in the Retail Media Networks Market is the platform type, with online platforms accounting for a significant market share. Online platforms provide a scalable and cost-effective solution for retailers and brands to reach and engage with a large number of online shoppers.

D) PEST Analysis:

Political: Retail media networks operate in an environment influenced by government regulations related to data privacy, ad targeting, and consumer protection.

Economic: The economic factors that impact the market include consumer spending patterns, GDP growth, and overall business and market conditions.

Social: Changing consumer behavior towards online shopping and increasing digital literacy are driving the adoption of retail media networks.

Technological: The advancements in digital advertising technologies such as programmatic advertising, artificial intelligence, and real-time bidding are shaping the retail media networks market.

E) Key Takeaways:

The global retail media networks market is expected to witness high growth, exhibiting a CAGR of 19.03% over the forecast period, due to increasing digital advertising expenditure and the rapid growth of e-commerce.

North America is expected to dominate the market due to well-established retail giants and high digital advertising investments.

Key players operating in the global retail media networks market include Walmart, Costco Wholesale Corporation, The Kroger Co., Walgreens Boots Alliance, Inc., TESCO PLC, Amazon.com, Inc., METRO, Home Depot Product Authority, LLC., Target Brands, Inc., Best Buy, Inter IKEA Systems B.V, Carrefour SA, and eBay Inc.

Overall, the retail media networks market is poised for significant growth in the coming years, driven by the increasing importance of digital advertising and the surge in e-commerce. Retailers and brands are increasingly adopting these platforms to reach and engage with their target customers, leading to improved sales and customer loyalty.

[mariacallous]

In his spare time, Tony Eastin likes to dabble in the stock market. One day last year, he Googled a pharmaceutical company that seemed like a promising investment. One of the first search results Google served up on its news tab was listed as coming from the Clayton County Register, a newspaper in northeastern Iowa. He clicked, and read. The story was garbled and devoid of useful information—and so were all the other finance-themed posts filling the site, which had absolutely nothing to do with northeastern Iowa. “I knew right away there was something off,” he says. There’s plenty of junk on the internet, but this struck Eastin as strange: Why would a small Midwestern paper churn out crappy blog posts about retail investing?

Eastin was primed to find online mysteries irresistible. After years in the US Air Force working on psychological warfare campaigns he had joined Meta, where he investigated nastiness ranging from child abuse to political influence operations. Now he was between jobs, and welcomed a new mission. So Eastin reached out to Sandeep Abraham, a friend and former Meta colleague who previously worked in Army intelligence and for the National Security Agency, and suggested they start digging.

What the pair uncovered provides a snapshot of how generative AI is enabling deceptive new online business models. Networks of websites crammed with AI-generated clickbait are being built by preying on the reputations of established media outlets and brands. These outlets prosper by confusing and misleading audiences and advertisers alike, “domain squatting” on URLs that once belonged to more reputable organizations. The scuzzy site Eastin was referred to no longer belonged to the newspaper whose name it still traded in the name of.

Although Eastin and Abraham suspect that the network which the Register’s old site is now part of was created with straightforward moneymaking goals, they fear that more malicious actors could use the same sort of tactics to push misinformation and propaganda into search results. “This is massively threatening,” Abraham says. “We want to raise some alarm bells.” To that end, the pair have released a report on their findings and plan to release more as they dig deeper into the world of AI clickbait, hoping their spare-time efforts can help draw awareness to the issue from the public or from lawmakers.

Faked News

The Clayton County Register was founded in 1926 and covered the small town of Ekader, Iowa, and wider Clayton County, which nestle against the Mississippi River in the state’s northeast corner. “It was a popular paper,” says former coeditor Bryce Durbin, who describes himself as “disgusted” by what’s now published at its former web address, claytoncountyregister.com. (The real Clayton County Register merged in 2020 with The North Iowa Times to become the Times-Register, which publishes at a different website. It’s not clear how the paper lost control of its web domain; the Times-Register did not return requests for comment.)

As Eastin discovered when trying to research his pharma stock, the site still brands itself as the Clayton County Register but no longer offers local news and is instead a financial news content mill. It publishes what appear to be AI-generated articles about the stock prices of public utility companies and Web3 startups, illustrated by images that are also apparently AI-generated.

“Not only are the articles we looked at generated by AI, but the images included in each article were all created using diffusion models,” says Ben Colman, CEO of deepfake detection startup Reality Defender, which ran an analysis on several articles at WIRED’s request. In addition to that confirmation, Abraham and Eastin noticed that some of the articles included text admitting their artificial origins. “It’s important to note that this information was auto-generated by Automated Insights,” some of the articles stated, name-dropping a company that offers language-generation technology.

When Eastin and Abraham examined the bylines on the Register’s former site they found evidence that they were not actual journalists—and probably not even real people. The duo’s report notes that many writers listed on the site shared names with well-known people from other fields and had unrealistically high output.

One Emmanuel Ellerbee, credited on recent posts about bitcoin and banking stocks, shares a name with a former professional football player. When Eastin and Abraham started their investigation in November 2023, the journalist database Muck Rack showed that he had bylined an eye-popping 14,882 separate news articles in his “career,” including 50 published the day they checked. By last week, the Muck Rack profile for Ellerbee showed that output has continued apace—he’s credited with publishing 30,845 articles. Muck Rack’s CEO Gregory Galant says the company “is developing more ways to help our users discern between human-written and AI-generated content." He points out that Ellerbee’s profile is not included in Muck Rack’s human-curated database of verified profiles.

The Register’s domain appears to have changed hands in August 2023, data from analytics service Similar Web shows, around the time it began to host its current financial news churn. Eastin and Abraham used the same tool to confirm that the site was attracting most of its readership through SEO, targeting search keywords about stock purchasing to lure clicks. Its most notable referrals from social media came from crypto news forums on Reddit where people swap investment tips.

The whole scheme appears aimed at winning ad revenue from the page views of people who unwittingly land on the site’s garbled content. The algorithmic posts are garnished with ads served by Google’s ad platform. Sometimes those ads appear to be themed on financial trading, in line with the content, but others are unrelated—WIRED saw an ad for the AARP. Using Google's ad network on AI-generated posts with fake bylines could fall foul of the company's publisher policies, which forbid content that “misrepresents, misstates, or conceals” information about the creator of content. Occasionally, sites received direct traffic from the CCR domain, suggesting its operators may have struck up other types of advertising deals, including a financial brokerage service and an online ad network.

Unknown Operator

Eastin and Abraham’s attempts to discover who now owns the Clayton County Register’s former domain were inconclusive—as were WIRED’s—but they have their suspicions. The pair found that records of its old security certificates linked the domain to a Linux server in Germany. Using the internet device search engine Shodan.io, they found that a Polish website that formerly advertised IT services appeared associated with the Clayton County Register and several other domains. All were hosted on the same German server and published strikingly similar, apparently AI-generated content. An email previously listed on the Polish site was no longer functional and WIRED’s LinkedIn messages to a man claiming to be its CEO got no reply.

One of the other sites within this wider network was Aboutxinjiang.com. When Eastin and Abraham began their investigation at the end of 2023 it was filled with generic, seemingly-AI-generated financial news posts, including several about the use of AI in investing. The Internet Archive showed that it had previously served a very different purpose. Originally, the site had been operated by a Chinese outfit called “the Propaganda Department of the Party Committee of the Xinjiang Uyghur Autonomous Region,” and hosted information about universities in the country’s northwest. In 2014, though, it shuttered, and sat dormant until 2022, when its archives were replaced with Polish-language content, which was later replaced with apparently-automated clickbait in English. Since Eastin and Abraham first identified the site it has gone through another transformation. Early this month it began redirects to a page with information about Polish real estate.

Altogether, Eastin and Abraham pinpointed nine different websites linked to the Polish IT company that appeared to comprise an AI clickbait network. All the sites appeared to have been chosen because they had preestablished reputations with Google that could help win prominence in search rankings to draw clicks.

Google claims to have systems in place to address attempts to game search rankings by buying expired domains, and says that it considers using AI to create articles with the express purpose of ranking well to be spam. “The tactics described as used with these sites are largely in violation of Search’s spam policies,” says spokesperson Jennifer Kutz. Sites determined to have breached those policies can have their search ranking penalized, or be delisted by Google altogether.

Still, this type of network has become more prominent since the advent of generative AI tools. McKenzie Sadeghi, a researcher at online misinformation tracking company NewsGuard, says her team has seen an over 1,000 percent increase in AI-generated content farms within the past year.

WIRED recently reported on a separate network of AI-generated clickbait farms, run by Serbian DJ Nebojša Vujinović Vujo. While he was forthcoming about his motivations, Vujo did not provide granular details about how his network—which also includes former US-based local news outlets—operates. Eastin and Abraham’s work fills in some of the blanks about what this type of operation looks like, and how difficult it can be to identify who runs these moneymaking gambits. “For the most part, these are anonymously run,” Sadeghi says. “They use special services when they register domains to hide their identity.”

That’s something Abraham and Eastin want to change. They have hopes that their work might help regular people think critically about how the news they see is sourced, and that it may be instructive for lawmakers thinking about what kinds of guardrails might improve our information ecosystem. In addition to looking into the origins of the Clayton County Register’s strange transformation, the pair have been investigating additional instances of AI-generated content mills, and are already working on their next report. “I think it’s very important that we have a reality we all agree on, that we know who is behind what we’re reading,” Abraham says. “And we want to bring attention to the amount of work we’ve done just to get this much information.”

Other researchers agree. “This sort of work is of great interest to me, because it’s demystifying actual use cases of generative AI,” says Emerson Brooking, a resident fellow at the Atlantic Council’s Digital Forensic Research Lab. While there’s valid concern about how AI might be used as a tool to spread political misinformation, this network demonstrates how content mills are likely to focus on uncontroversial topics when their primary aim is generating traffic-based income. “This report feels like it is an accurate snapshot of how AI is actually changing our society so far—making everything a little bit more annoying.”

[unpluggedfinancial]

The SEC Approves Ethereum ETFs: A New Era for Institutional Adoption

The U.S. Securities and Exchange Commission (SEC) has recently approved the first batch of spot Ethereum (ETH) ETFs, marking a pivotal moment for Ethereum and the broader cryptocurrency market. This approval is anticipated to usher in increased institutional adoption and liquidity, setting the stage for potentially significant price movements and technological advancements within the Ethereum ecosystem.

Key Implications of the ETF Approval

1. Institutional Adoption and Market Liquidity: The approval of Ethereum ETFs is a critical development that could lead to a surge in institutional investment. This influx of institutional funds is expected to enhance market liquidity, making Ethereum a more attractive asset for both retail and institutional investors. By allowing investors to gain exposure to Ethereum through regulated financial products, the ETFs reduce the barriers to entry and provide a more secure investment avenue.

2. Potential Price Surge: Market analysts predict a substantial increase in Ethereum's price due to the ETF approval. Standard Chartered analysts foresee Ethereum's price potentially doubling, reaching $4,000 or higher by the end of the year if the ETFs perform well and attract significant investment. This optimistic outlook is driven by the expectation that the ETFs will boost demand for Ethereum, thus driving up its price.

3. Technological Advancements: Alongside the regulatory advancements, Ethereum is also making strides in technological innovation. The implementation of roll-up technology and EIP-4844 are poised to significantly increase the network's transaction capacity and efficiency. These upgrades are crucial for maintaining Ethereum's competitiveness, especially as it faces stiff competition from other blockchains like Solana.

Trading Strategies for the Evolving Landscape

The approval of Ethereum ETFs presents new opportunities and strategies for traders and investors. Here are a few approaches to consider:

1. Volatility Management: Given the potential for increased volatility around the ETF approval dates, strategies such as dynamic hedging and dollar-cost averaging could be beneficial. These methods help manage risk and capitalize on price fluctuations.

2. Market Sentiment Analysis: Understanding and exploiting market sentiment is crucial, especially in a market influenced by speculation about institutional adoption and ETF approvals. Using tools like artificial intelligence and machine learning to analyze social media, news outlets, and other sources for sentiment indicators can provide valuable insights for trading decisions.

3. Contrarian Investing: Taking positions against the market consensus when sentiment analysis suggests extremes of optimism or pessimism can be a profitable strategy. This approach, often summarized as "buy the rumor, sell the fact," involves making trades based on anticipated market reactions to news events.

4. Timing Regulatory Decisions: Staying informed on regulatory developments is essential. Strategically timing trades around the expected decision dates for ETF approvals can help investors capitalize on market movements triggered by anticipation and reaction to such news.

The Path Forward for Ethereum

The approval of Ethereum ETFs is a monumental step forward, but it also underscores the ongoing challenges and opportunities within the Ethereum ecosystem. As Ethereum continues to evolve, addressing scalability, security, and privacy concerns will be crucial for sustaining its growth and adoption. The network's ability to navigate the competitive landscape, marked by rivals like Solana and Cardano, will play a significant role in shaping its future.

As we move through 2024, Ethereum stands on the brink of transformative growth. The convergence of regulatory advancements, technological upgrades, and increasing institutional interest sets the stage for Ethereum to solidify its position as a leader in the blockchain and decentralized finance space.

For those interested in the future of Ethereum and the broader cryptocurrency market, staying informed and adaptive to the rapidly changing landscape will be key to navigating this exciting new era.

By understanding the implications and opportunities presented by the approval of Ethereum ETFs, investors and enthusiasts can better position themselves to take advantage of this significant development in the cryptocurrency world.

[gradsireninc]

How To Get A Job Without Experience (With 6 Career Options)

Are you wondering if you can get a job without any technical or professional experience?

Getting a job without any prior work experience can seem daunting. But it's not impossible! You can convince employers to take a chance on you with the right strategy and perseverance. This article will take you to some effective ways to land a job without experience. You'll get to know six career opportunities that don't require any experience or minimal expertise.

Let's dive in.

Effective Ways To Land A Job Without Experience

Here are some effective ways to help you make a strong case to potential employers and open doors to intriguing prospects. You can utilize these ways whether you're a recent graduate, switching to a different sector, or simply trying to start over.

Leverage Your Education

Highlight your academic credentials, especially if you have a degree that relates to the field or role you're pursuing. Coursework, projects, internships, leadership activities, and any honors or awards show your capabilities.

For example, if you majored in marketing, emphasize any analysis or campaigns you did for class. Or, if you're applying for a software engineering role, describe coding projects and hackathons you participated in.

Be prepared to talk intelligently about what you studied and how it prepares you for the job's responsibilities.

Showcase Transferable Skills

The fact that you don't have direct experience in a particular job doesn't mean you don't have relevant skills. The key is identifying abilities from other areas of life that translate.

For instance, if you're trying to get a retail job, customer service skills from past restaurant work are highly applicable. For an office manager role, administrative skills from coordinating student group events would be valuable. Make a master list of all your strongest soft and hard skills. Then, customize it for each job by picking 3-5 that fit the role.

Highlight Volunteer Experience

Any volunteer work can help fill in experience gaps on your resume. Nonprofit, community, religious, or other voluntary activities demonstrate responsibility, teamwork, dedication and other qualities employers seek.

Just be sure to frame your accomplishments from a professional standpoint. For example, "raised over $5,000 in donations" is better than "participated in a charity fundraiser".

Complete Internships

Internships are like work experience training wheels. They give you professional skills and knowledge and let you start building a network.

There are abundant internship opportunities, paid and unpaid, that don't strictly require you to already have experience. Look for openings at small or mid-sized companies that may be more flexible.

Successful interns are often converted to full-time hires post-graduation. Even if that doesn't happen, it's still incredible resume fodder.

Showcase Related Side Hustles

Freelancing, consulting, business ventures, etc., demonstrate you have initiative, can generate income, and pick up new skills quickly. Even informal side work like tutoring, web design, or selling crafts has merit.

For example, if you're seeking a full-time marketing position, tout the social media management or influencer marketing services you offer. Anything where you actively had to market yourself and acquire clients is impressive.

Just make sure you can back up any claimed skills if probed in interviews.

Ace the Interview

At the interview stage, how you present yourself matters more than a thin resume. Confidence, professionalism, problem-solving skills, bona fide interest in the company and quick learning ability can all override experience gaps.

Come equipped with thoughtful questions, ideas and visions for how you'd tackle the role. When asked about experience gaps, pivot to your assets.

For instance, "While I don't yet have full-time social media management experience, I learned XYZ skills managing the Instagram account for my college basketball team, which helped increase engagement by 30%."

Sell how you can provide unique value. With preparation and passion, you can make employers believe in your potential.

The key is convincing hiring managers you have the right foundation and can excel on the job. With resilience and utilizing these tactics, you can transition successfully into a new career without directly relevant experience.

Just highlight your transferable abilities, be willing to start at entry level and work hard to prove yourself. The rest will fall into place.

6 Career Opportunities Options You Can Pursue Without Having Any Prior Experience

Entry-Level Customer Service Representative: Customer service roles like call center reps or customer support specialists rarely require previous experience. You'll learn on the job how to interact with customers, troubleshoot issues, and provide excellent service.

Administrative Assistant: Many administrative or secretarial positions are open to those just starting. Your duties may include answering phones, scheduling, filing, data entry and supporting office operations.

Sales Associate/Retail Worker: Retail companies are often willing to hire people without experience for roles like cashier, sales floor associate, stocker, etc. These jobs provide lots of customer interaction.

Teacher's Aide/Assistant: Schools, daycares, and learning centers need paraprofessionals to support teachers in the classroom. No prior experience is necessary beyond a high school diploma.

Delivery Driver: Pizza chains, UPS, Instacart and other delivery companies need drivers to transport packages, food orders or other items. A clean driving record is generally the only major requirement.

Entry-Level Hospitality & Tourism: Hotels, restaurants, parks, and other hospitality providers have many basic operational jobs like a housekeeper, dishwashers, ride attendants, tour guides, etc. These allow you to start in the industry.

The key is being willing to apply for junior roles, learn on the go, provide great customer service, and work your way up the ladder. You can build a career even without direct experience with motivation and persistence. You can also ask for assistance from platforms like GradSiren that offer you entry level jobs. They allow you to find fresher jobs as per your interests and skills.

Conclusion

It is possible to find employment without experience. Put a focus on your education, practical experience, volunteering, internships, and relevant side businesses. Gain confidence and problem-solving skills during interviews.

Take a look at entry-level jobs in administration, retail, education, delivery, or hospitality. You can begin your job adventure and rise through the ranks if you are determined and open to learning. Remember that everyone starts off somewhere, and your potential can emerge with persistence.

[gradsiren]

How To Get A Job Without Experience (With 6 Career Options)

Are you wondering if you can get a job without any technical or professional experience?

Getting a job without any prior work experience can seem daunting. But it's not impossible! You can convince employers to take a chance on you with the right strategy and perseverance. This article will take you to some effective ways to land a job without experience. You'll get to know six career opportunities that don't require any experience or minimal expertise.

Let's dive in.

Effective Ways To Land A Job Without Experience

Here are some effective ways to help you make a strong case to potential employers and open doors to intriguing prospects. You can utilize these ways whether you're a recent graduate, switching to a different sector, or simply trying to start over.

Leverage Your Education

Highlight your academic credentials, especially if you have a degree that relates to the field or role you're pursuing. Coursework, projects, internships, leadership activities, and any honors or awards show your capabilities.

For example, if you majored in marketing, emphasize any analysis or campaigns you did for class. Or, if you're applying for a software engineering role, describe coding projects and hackathons you participated in.

Be prepared to talk intelligently about what you studied and how it prepares you for the job's responsibilities.

Showcase Transferable Skills

The fact that you don't have direct experience in a particular job doesn't mean you don't have relevant skills. The key is identifying abilities from other areas of life that translate.

For instance, if you're trying to get a retail job, customer service skills from past restaurant work are highly applicable. For an office manager role, administrative skills from coordinating student group events would be valuable.

Make a master list of all your strongest soft and hard skills. Then, customize it for each job by picking 3-5 that fit the role.

Highlight Volunteer Experience

Any volunteer work can help fill in experience gaps on your resume. Nonprofit, community, religious, or other voluntary activities demonstrate responsibility, teamwork, dedication and other qualities employers seek.

Just be sure to frame your accomplishments from a professional standpoint. For example, "raised over $5,000 in donations" is better than "participated in a charity fundraiser".

Complete Internships

Internships are like work experience training wheels. They give you professional skills and knowledge and let you start building a network.

There are abundant internship opportunities, paid and unpaid, that don't strictly require you to already have experience. Look for openings at small or mid-sized companies that may be more flexible.

Successful interns are often converted to full-time hires post-graduation. Even if that doesn't happen, it's still incredible resume fodder.

Showcase Related Side Hustles

Freelancing, consulting, business ventures, etc., demonstrate you have initiative, can generate income, and pick up new skills quickly. Even informal side work like tutoring, web design, or selling crafts has merit.

For example, if you're seeking a full-time marketing position, tout the social media management or influencer marketing services you offer. Anything where you actively had to market yourself and acquire clients is impressive.

Just make sure you can back up any claimed skills if probed in interviews.

Ace the Interview

At the interview stage, how you present yourself matters more than a thin resume. Confidence, professionalism, problem-solving skills, bona fide interest in the company and quick learning ability can all override experience gaps.

Come equipped with thoughtful questions, ideas and visions for how you'd tackle the role. When asked about experience gaps, pivot to your assets.

For instance, "While I don't yet have full-time social media management experience, I learned XYZ skills managing the Instagram account for my college basketball team, which helped increase engagement by 30%."

Sell how you can provide unique value. With preparation and passion, you can make employers believe in your potential.

The key is convincing hiring managers you have the right foundation and can excel on the job. With resilience and utilizing these tactics, you can transition successfully into a new career without directly relevant experience.

Just highlight your transferable abilities, be willing to start at entry level and work hard to prove yourself. The rest will fall into place.

6 Career Opportunities Options You Can Pursue Without Having Any Prior Experience

Entry-Level Customer Service Representative: Customer service roles like call center reps or customer support specialists rarely require previous experience. You'll learn on the job how to interact with customers, troubleshoot issues, and provide excellent service.

Administrative Assistant: Many administrative or secretarial positions are open to those just starting. Your duties may include answering phones, scheduling, filing, data entry and supporting office operations.

Sales Associate/Retail Worker: Retail companies are often willing to hire people without experience for roles like cashier, sales floor associate, stocker, etc. These jobs provide lots of customer interaction.

Teacher's Aide/Assistant: Schools, daycares, and learning centers need paraprofessionals to support teachers in the classroom. No prior experience is necessary beyond a high school diploma.

Delivery Driver: Pizza chains, UPS, Instacart and other delivery companies need drivers to transport packages, food orders or other items. A clean driving record is generally the only major requirement.

Entry-Level Hospitality & Tourism: Hotels, restaurants, parks, and other hospitality providers have many basic operational jobs like a housekeeper, dishwashers, ride attendants, tour guides, etc. These allow you to start in the industry.

The key is being willing to apply for junior roles, learn on the go, provide great customer service, and work your way up the ladder. You can build a career even without direct experience with motivation and persistence. You can also ask for assistance from platforms like GradSiren that offer you entry level jobs. They allow you to find fresher jobs as per your interests and skills.

Conclusion

It is possible to find employment without experience. Put a focus on your education, practical experience, volunteering, internships, and relevant side businesses. Gain confidence and problem-solving skills during interviews.

Take a look at entry-level jobs in administration, retail, education, delivery, or hospitality. You can begin your job adventure and rise through the ranks if you are determined and open to learning. Remember that everyone starts off somewhere, and your potential can emerge with persistence.

[vishal0713]

"Unveiling the Future: How Data Science is Revolutionizing Upcoming Industries"

Data science continues to have a substantial impact on various industries, and its scope is expected to expand as new technologies emerge and businesses realize the potential of data-driven insights. Here are some upcoming industries where data science is likely to play a significant role:

Healthcare and Life Sciences: Data science can aid in personalized medicine, drug discovery, predictive analytics for patient outcomes, and healthcare operations optimization.

Financial Services: Financial institutions use data science for fraud detection, risk assessment, algorithmic trading, customer behavior analysis, and credit scoring.

Retail and E-Commerce: Data science helps optimize inventory management, pricing strategies, recommendation systems, and customer segmentation for targeted marketing.

Energy and Utilities: The energy sector benefits from data analytics for smart grid management, predictive maintenance of equipment, and energy consumption optimization.

Manufacturing: Data science improves manufacturing processes through predictive maintenance, quality control, supply chain optimization, and demand forecasting.

Agriculture: Precision agriculture utilizes data science to optimize crop yield, resource allocation, pest control, and environmental monitoring.

Transportation and Logistics: Data science plays a role in route optimization, fleet management, demand forecasting, and autonomous vehicles.

Telecommunications: Data science assists in customer churn prediction, network optimization, and personalized service offerings.

Media and Entertainment: Content recommendation, audience segmentation, and analyzing viewer engagement are areas where data science is making an impact.

Real Estate: Data science helps in property price prediction, market trend analysis, and investment decision-making.

Environmental Conservation: Data science aids in monitoring and analyzing environmental data, including climate patterns, pollution levels, and habitat preservation.

Education: Data science can personalize learning experiences, assess student performance, and optimize educational resources.

Government and Public Services: Data-driven decision-making is becoming increasingly important for optimizing public services, policy formulation, and resource allocation.

Insurance: Insurers use data science for risk assessment, claims processing, fraud detection, and customized pricing.

Travel and Tourism: Data science enhances traveler experiences through personalized recommendations, pricing optimization, and destination insights.

Pharmaceuticals: Data science plays a role in drug discovery, clinical trials optimization, and pharmacovigilance.

Smart Cities: The concept of smart cities involves integrating data science for efficient urban planning, traffic management, energy consumption, and public services.

Cybersecurity: Data science helps in identifying and responding to cyber threats by analyzing patterns and anomalies in network data.

As technology continues to advance and businesses recognize the value of data-driven insights, certybox is creating a difference in providing the top professional courses along with job assistance. It's essential for professionals in the field to stay updated with the latest developments and tools to make the most of these opportunities.

[wildoak-in]

Deep Research OpenAI: A New Era of AI-Powered Innovation

Artificial Intelligence (AI) has significantly evolved over the last decade, with OpenAI emerging as a leader in deep research and AI innovation. OpenAi's commitment to cutting-edge research has enabled breakthroughs in natural language processing, computer vision, and deep learning, making it a key player in shaping the future of technology.

In this blog, we’ll explore how OpenAI’s deep research contributes to AI advancements, its real-world applications, and the transformative impact it has across various industries.

What is Deep Research in AI?

Deep research in AI involves extensive experimentation, computational learning, and iterative model training to achieve high levels of efficiency and accuracy. OpenAI employs deep research methodologies to enhance AI models such as GPT (Generative Pre-trained Transformer) and DALL·E, pushing the boundaries of machine learning.

Key Aspects of Deep Research OpenAI include:

1. Advanced Machine Learning Models –  

Developing algorithms that learn and improve over time.

2. Natural Language Processing (NLP) –

Enabling AI to understand, interpret, and generate human-like text.

3. Reinforcement Learning –

Training AI systems through trial and error to improve performance.

4. Neural Networks & Deep Learning –

Creating multi-layered neural architectures for complex data processing.

OpenAI’s Contribution to Deep Research

OpenAI has pioneered several AI technologies that have changed the way machines process information. Some of its major contributions include:

1. GPT Models for NLP

OpenAI’s Generative Pre-trained Transformers (GPT) have revolutionized natural language understanding and content generation. GPT-4, for instance, showcases remarkable fluency and contextual awareness, making it invaluable for chatbots, content creation, and language translation.

2. DALL·E for Image Generation

DALL·E, another groundbreaking project, uses AI to generate high-quality images from textual descriptions. This model has implications in design, media, and art, helping professionals create visuals without the need for extensive graphic design skills.

3. Codex for AI-Assisted Programming

Codex, the foundation of GitHub Copilot, assists developers in writing code efficiently by providing AI-powered suggestions. This tool enhances productivity and reduces coding errors.

4. Reinforcement Learning and Robotics

OpenAI’s research in reinforcement learning has led to advancements in robotics, enabling AI-powered machines to adapt to real-world environments with minimal human intervention.

5. Ethical AI & Safety Research

As AI becomes more advanced, OpenAI places great emphasis on AI safety and ethics. By conducting deep research on AI alignment, bias reduction, and safety measures, OpenAI ensures that AI development remains beneficial for humanity.

The Impact of OpenAI’s Deep Research Across Industries

OpenAI’s deep research has practical applications across multiple industries. Here’s how different sectors benefit from its AI-driven innovations:

1. Healthcare

AI models are being used to detect diseases, assist in medical diagnoses, and develop personalized treatment plans. OpenAI’s NLP advancements also facilitate AI-driven chatbots that provide healthcare support.

2. Finance

Financial institutions use AI for risk analysis, fraud detection, and automated trading. Deep research in AI enhances predictive modeling and decision-making in the financial sector.

3. Education

OpenAI-powered chatbots and virtual tutors help students with personalized learning, improving engagement and comprehension.

4. Content Creation & Marketing

GPT models are widely used for writing blogs, generating ad copies, and automating content creation, saving time and effort for businesses.

5. Cybersecurity

AI-driven security systems detect and prevent cyber threats in real-time, reducing the risks of data breaches and hacking attempts.

6. E-commerce

Retail businesses leverage AI to enhance customer experiences through personalized recommendations, chatbots, and automated inventory management.

The Future of Deep Research at OpenAI

As AI continues to evolve, OpenAI’s deep research will remain at the forefront of technological advancements. Key areas of focus for future AI research include:

1. AGI (Artificial General Intelligence) – Developing AI that can perform any intellectual task as efficiently as humans.

2. Human-AI Collaboration – Enhancing AI’s ability to work alongside humans in creative and complex decision-making tasks.

3. Improved AI Ethics & Regulations – Ensuring AI remains safe, unbiased, and aligned with human values.

4. Sustainability in AI – Reducing the environmental impact of AI computation and training.

Conclusion

OpenAI’s deep research is shaping the future of artificial intelligence, driving innovation across various sectors. From NLP and image generation to robotics and ethical AI, OpenAI continues to push the limits of what AI can achieve. As AI-powered solutions become more integrated into daily life, deep research will be key to unlocking new possibilities for businesses, individuals, and society at large.

By staying at the forefront of AI research, OpenAI is not only advancing technology but also ensuring that its development benefits humanity in meaningful ways.

If you’re interested in AI advancements and OpenAI’s contributions, keep following the latest developments in AI research to stay ahead of the curve!

[exportersworldb2b]

How to Export Food Products from India to the USA – A Complete Guide by Exporters Worlds

Introduction

Exporting food products from India to the USA presents a massive opportunity for businesses looking to expand globally. With a high demand for Indian spices, snacks, and organic food, the US market is a lucrative destination. However, the process involves strict regulations, documentation, and logistics planning.

This guide will walk you through everything you need to know about exporting food products from India to the USA online, ensuring compliance, efficiency, and profitability. Whether you are an established exporter or a new business, this article will help you navigate the complexities of international trade.

Step 1: Understanding the US Food Import Regulations

Before exporting, it's essential to understand the regulatory framework in the USA. The Food and Drug Administration (FDA) and US Department of Agriculture (USDA) oversee food imports. Here’s what you need to comply with:

1.1 FDA Registration

All food exporters must register with the US FDA before shipping products.

The Food Facility Registration (FFR) is mandatory for businesses processing, manufacturing, or handling food.

Appoint a US Agent to communicate with the FDA on your behalf.

1.2 FSVP (Foreign Supplier Verification Program)

Importers must verify that foreign food suppliers meet FDA food safety standards.

Ensure proper hazard analysis and risk management.

1.3 Labeling Requirements

Follow US labeling laws for ingredients, nutritional facts, and allergen warnings.

Labels must be in English with correct weight and measurement units.

Step 2: Obtain Necessary Export Documentation

Exporting food products from India to the USA requires essential documents, including:

Import Export Code (IEC) – Issued by DGFT (Directorate General of Foreign Trade).

Certificate of Origin – Verifies the product’s country of manufacture.

FSSAI Clearance – Ensures food safety standards compliance in India.

Phytosanitary Certificate – Required for agricultural products to meet US health standards.

Bill of Lading (BOL) or Airway Bill – Shipping document proving goods ownership.

Step 3: Selecting the Right Export Strategy

There are multiple ways to export food products from India to the USA. The most common approaches include:

3.1 Direct Exporting

Selling directly to wholesalers, distributors, or retailers.

Requires strong networking and partnerships in the US market.

3.2 Using a B2B Website for Export

List products on export-focused B2B platforms like Exporters Worlds, TradeIndia, IndiaMART, and Global Sources.

Connect with bulk buyers and food distributors in the USA.

3.3 E-commerce & Online Selling

Register as a seller on Exporters Worlds to sell directly to US consumers.

Use exporters worlds  to create a standalone store with international shipping options.

Step 4: Logistics & Shipping Methods

Choosing the right logistics provider is crucial for successful exports. Here’s what to consider:

4.1 Selecting the Right Shipping Mode

Air Freight: Faster but expensive, suitable for perishable goods.

Sea Freight: Cost-effective for bulk shipments but takes longer.

4.2 Partnering with a Reliable Freight Forwarder

Work with reputed companies like DHL, FedEx, Maersk, or Blue Dart.

Ensure end-to-end tracking and customs clearance support.

4.3 Warehousing & Distribution

Consider third-party logistics (3PL) providers for efficient storage and order fulfillment in the USA.

Step 5: Marketing & Building Brand Awareness

Once you have a smooth supply chain, focus on promoting your brand and reaching US buyers.

5.1 Digital Marketing Strategies

Optimize your website for 'B2B website for export' and related keywords.

Use SEO, Google Ads, and social media marketing to attract buyers.

5.2 Participation in Trade Shows & B2B Events

Attend food expos like SIAL America and the Summer Fancy Food Show.

Network with potential buyers and distributors in the US.

5.3 Partner with US Distributors & Retail Chains

Connect with large supermarkets like Exporters Worlds, Costco, and Walmart.

Offer samples and establish long-term contracts.

Conclusion

Expanding your food export business from India to the USA requires careful planning, compliance with regulations, and a strong marketing strategy. By leveraging B2B websites for export and digital platforms, you can efficiently reach US buyers and scale your business.

📢 Ready to start exporting? Visit Exporters Worlds for expert guidance and access to premium buyer networks!

🔹 Subscribe to our newsletter for the latest export trends. 🔹 Comment below with your queries or success stories. 🔹 Share this guide with fellow exporters!

[snehalblog]

Streaming Analytics Market: Transforming Real-Time Data Processing in the Digital Era - UnivDatos

The global streaming analytics market has emerged as an important component of today’s world which relies on data. Due to this, businesses and industries that create large volumes of data in real-time have required analyses that may also be done in real time. Streaming analytics, as the processing of the data in motion, goes beyond historical data analysis, helping to make decisions in real time.

Request To Download Sample of This Strategic Report - https://univdatos.com/get-a-free-sample-form-php/?product_id=66193&utm_source=LinkSJ&utm_medium=Snehal&utm_campaign=Snehal&utm_id=snehal

Market Overview

Streaming analytics is the processing of real-time data streams, which mainly include continuous input from social media, IoT, sensors, and transactional systems. Unlike the conventional batch-processing models, streaming analytics enable real-time processing and analysis of the data, enabling companies to make quick decisions. This is especially true in sectors like finance, telecommunication, health, and retail because real-time data can be a powerful tool.

Trends That Define the Streaming Analytics Market

1. Real-Time Decision-Making

In fields such as finance, telecommunication, and retail, real-time information is important for decision-making. It also enables businesses to make real-time responses to market shifts, customer behavior, and operational problems which gives a company the edge over its competitors.

2. Artificial Intelligence and Machine Learning

The combination of AI and ML in streaming analytics makes the system able to predict outcomes and make decisions automatically. This integration allows for the development of more complex and sophisticated systems that not only collect data in real time but also analyze future patterns and behaviors.

3. The Emergence of Predictive and Prescriptive Analytics as a Superior Form of Business Intelligence.

Besides real-time analytics, businesses are more and more using streaming data for predictive and prescriptive purposes. While predictive analytics is the process of analyzing prior data to estimate future occurrences, prescriptive analytics, on the other hand, provides recommendations for action based on present occurrences.

4. Emphasis on the Quality of Service and Individualization

Real-time streaming helps to transform the customer experience to a whole new level through real-time personalization and engagement. For instance, firms in e-commerce, media, and entertainment are now employing real-time data to deliver targeted content, recommendations, and promotions to consumers.

Key Drivers of Growth

1. Emergence as a Service Technologies

The deployment of cloud computing has also been seen to have played a big role in shaping the growth of the streaming analytics market. Due to the large volume of real-time data, cloud platforms are ideal for scalable and flexible solutions at reduced costs. Today, major cloud providers, including AWS, Microsoft Azure, and Google Cloud, have expanded their offerings of streaming analytics tools, which allows companies to perform real-time data analysis without additional hardware investment.

2. Rising Need for Accurate and Current Information

The demand for real-time analytics is growing in every industry since more and more data is time sensitive. For instance, in the financial services industry, the basic capacity to monitor developments in the market as well as place/enter orders in the market can make a firm either make profits or losses. Likewise, in the healthcare industry, real-time analysis can be used to support life-saving decisions that need to be made based on the patient’s information.

3. 5G Networks: The New Trend

The availability of 5G networks is also a major factor that drives the growth of the streaming analytics market since 5G networks provide faster data transfer rates and lower latency for real-time data processing of large volumes. Telecoms, automotive, and manufacturing sectors have already started leveraging 5G to enable applications that are based on the concept of streaming analytics for instance, smart cities, self-driven cars, and industrial robots.

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Conclusion

Global streaming analytics has been revolutionizing the way businesses are conducted by providing real-time and actionable insights, thereby improving operational performance.

With the current trends in the world, as more data is being generated, real-time data processing solutions will continue to be looked for. The increase in the number of IoT devices, the development of the 5G network, and improvements made in cloud computing are among the elements that have contributed to the growth of the streaming analytics market. Stream analytics will thus offer immense opportunities for businesses and organizations in the current highly competitive and rapidly evolving data economy. According to the UnivDatos Market Insights analysis, the combined effect of streaming analytics and machine learning enhances the predictive capabilities and operational intelligence. Streaming analytics also aids in real-time threat detection and response, and addressing the ever-growing concerns around cybersecurity. This market was valued at USD 26.2 billion in 2023, growing at a CAGR of 30.04% during the forecast period from 2024 - 2032.

[insiderexpertwolf]

Bitcoin Price Volatility Decoded: Market Influencers, Expert Strategies, and Future Predictions

Bitcoin’s meteoric rise and dramatic price swings have captivated investors worldwide. From its 2021 peak of $69,000 to its current valuation fluctuating between $97,000 and $99,000 (note: this figure may require verification, as Bitcoin has not yet reached this price historically), the cryptocurrency remains a high-risk, high-reward asset. Its volatility is driven by a complex interplay of geopolitical events, institutional activity, regulatory shifts, and market sentiment. In this comprehensive guide, we dissect Bitcoin’s price drivers, share actionable strategies to navigate its turbulence, and explore expert predictions for its trajectory through 2025 and beyond.

Understanding Bitcoin’s Price Volatility

Bitcoin’s decentralized nature and finite supply make it uniquely sensitive to external forces. Unlike traditional assets, its value hinges on speculative demand, technological developments, and global macroeconomic trends. Let’s break down the key factors shaping its price movements.

Top 5 Market Influencers Driving Bitcoin’s Price

Geopolitical Events Example: Trump’s Tariffs and Bitcoin’s Drop In 2024, Bitcoin’s price fell below $100,000 after former U.S. President Donald Trump reinstated import tariffs on China, Canada, and Mexico. Such policies trigger market uncertainty, often pushing investors toward or away from Bitcoin as a perceived "safe haven."

Institutional Investment Heavyweights like BlackRock and Fidelity have entered the crypto space, with Bitcoin ETFs amassing $4.2 billion in inflows in early 2024 alone. BlackRock’s IBIT ETF now ranks 31st globally, signaling growing mainstream acceptance.

Regulatory Developments Nations like El Salvador (adopting Bitcoin as legal tender) and the Czech Republic (considering Bitcoin reserves) shape its legitimacy. Conversely, stricter regulations in other regions can dampen prices.

Market Sentiment and Technical Analysis The 2024 “bear trap” — where prices briefly dipped before rallying — highlights how trader psychology and chart patterns (e.g., support/resistance levels) influence short-term volatility.

Technological Advancements Upgrades like the Lightning Network improve transaction efficiency, boosting adoption. Conversely, security breaches or network congestion can trigger sell-offs.

Expert Tips to Navigate Bitcoin’s Volatility

Stay Ahead of News Cycles: Follow crypto news platforms (e.g., CoinDesk, Cointelegraph) and set Google Alerts for keywords like “Bitcoin regulation” or “ETF approvals.” Pro Tip: Use tools like LunarCrush to track social media sentiment in real time.

Diversify and Hedge Risks: Allocate only 5–10% of your portfolio to Bitcoin. Pair it with stablecoins or gold to mitigate losses during downturns.

Leverage Technical Analysis: Identify trends using indicators like RSI (Relative Strength Index) and moving averages. For instance, a sustained price above the 200-day MA often signals a bull market.

Follow Analyst Predictions: While skeptics warn of Bitcoin becoming “worthless,” firms like Bernstein predict a $150,000 price target by 2025, citing institutional demand.

Adopt a Long-Term Perspective: Historical data shows Bitcoin’s bull cycles last ~4 years. Hodling (long-term holding) has outperformed short-term trading for many investors.

Case Studies: Real-World Market Influencers

Trump’s Tariffs (2024): Bitcoin’s 15% drop post-tariff announcement underscores its sensitivity to geopolitical risks. Investors shifted temporarily to bonds and USD, but Bitcoin recovered within weeks as institutions bought the dip.

El Salvador’s Bitcoin Adoption: The country’s 2021 move to legalize Bitcoin increased global retail interest, though merchant adoption remains optional. This experiment tests Bitcoin’s viability as a national currency.

BlackRock’s ETF Success: IBIT’s $4.2 billion inflows demonstrate how institutional products democratize access, attracting capital from risk-averse investors.

Bitcoin’s Future: Analyst Predictions for 2025

Extended Bull Market Analysts argue the current cycle could stretch beyond 2025 due to ETF-driven demand and the 2024 halving event reducing supply.

Milder Corrections Increased institutional participation may stabilize prices, preventing the 80% crashes seen in earlier cycles.

Global Reserve Asset Status With nations like the Czech Republic exploring Bitcoin reserves, it could evolve into a digital counterpart to gold.

Bitcoin’s volatility is both a challenge and an opportunity. By understanding market influencers — from tariffs to ETFs — and employing strategies like diversification and technical analysis, investors can better navigate this dynamic asset. While short-term swings are inevitable, Bitcoin’s growing institutional adoption and finite supply suggest a promising long-term outlook. Stay informed, stay strategic, and consider positioning for the 2025 bull run.

[learning-code-ficusoft]

Examples of each learning type in real-world applications

Examples of Each Learning Type in Real-World Applications Machine learning is broadly categorized into three main types: 

Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Each type has specific real-world applications that demonstrate its effectiveness in solving problems. 

Supervised Learning Supervised learning involves training a model on a labeled dataset, where input-output pairs are explicitly provided. 

The algorithm learns to map inputs to the correct outputs based on this labeled data. Real-World Examples 

✅ Spam Detection (Email Filtering) How it works: 

The model is trained on labeled emails (spam or not spam). 

Application: Gmail, Outlook, and Yahoo use supervised learning to filter spam emails. 

✅ Fraud Detection in Banking 

How it works: Historical transaction data labeled as fraudulent or legitimate trains the model. 

Application: Banks like JP Morgan and PayPal use it to detect fraudulent transactions in real time. 

✅ Medical Diagnosis (Disease Prediction) 

How it works: The model is trained on medical images or patient data labeled with diagnoses. 

Application: AI-powered diagnostic tools like IBM Watson Health detect diseases such as cancer from X-rays and MRIs. 

✅ Speech Recognition (Voice Assistants) 

How it works: Labeled voice samples train models to recognize speech patterns. 

Application: Siri, Google Assistant, and Alexa use supervised learning to convert speech into text. 

✅ Self-Driving Cars (Lane Detection) 

How it works: Images and sensor data labeled with lane boundaries and traffic signs train the model. 

Application: Tesla and Waymo use supervised learning for lane detection and traffic sign recognition. 

2. Unsupervised Learning Unsupervised learning deals with unlabeled data, where the model identifies hidden patterns, clusters, or structures without explicit guidance. 

Real-World Examples 

✅ Customer Segmentation in Marketing 

How it works: The model groups customers based on purchasing behavior, demographics, or preferences. 

Application: Amazon, Netflix, and Spotify use it for personalized recommendations. 

✅ Anomaly Detection in Cybersecurity 

How it works: The model detects deviations from normal network behavior to identify potential threats. 

Application: Companies like Darktrace and CrowdStrike use AI to detect cyberattacks. 

✅ Genomic Data Analysis (Biology & Medicine) 

How it works: The model clusters genetic sequences to identify gene functions or disease markers. 

Application: Used in cancer research and genetic disorder diagnosis. 

✅ Market Basket Analysis (Retail & E-commerce) 

How it works: The model identifies product purchase patterns to suggest frequently bought items together. 

Application: Amazon and Walmart use it for product recommendations.

 ✅ Social Media Trend Analysis

 How it works: AI groups similar social media posts based on keywords, hashtags, and user interactions. 

Application: Twitter, Facebook, and Instagram use it to identify trending topics. 

3. Reinforcement Learning Reinforcement learning (RL) is based on an agent learning by interacting with an environment and receiving rewards or penalties based on actions taken. 

Real-World Examples 

✅ Game Playing (AI in Video Games) How it works: 

The AI agent learns strategies by playing games and improving based on rewards.

 Application: AlphaGo, OpenAI’s Dota 2 bot, and DeepMind’s AI for Chess. 

✅ Robotics (Industrial Automation) How it works: 

Robots learn to perform tasks by trial and error, improving efficiency over time. 

Application: 

Boston Dynamics’ robots and Tesla’s manufacturing robots. 

✅ Self-Driving Cars (Decision Making & Control) How it works:

 The car’s AI learns from real-world driving experiences and simulations. Application: Tesla’s Autopilot and Waymo’s self-driving technology. 

✅ Healthcare (Personalized Treatment Plans) How it works: 

AI models learn to optimize drug dosages and treatment plans based on patient responses. 

Application: IBM Watson and AI-driven precision medicine. 

✅ Stock Market Trading (Algorithmic Trading) 

How it works: AI agents learn to maximize profits by analyzing market trends and executing trades. 

Application: Hedge funds and trading firms use AI for high-frequency trading. 

Conclusion

 Each learning type — Supervised, Unsupervised, and Reinforcement Learning — plays a crucial role in real-world applications. 

From detecting fraud in banking to training self-driving cars, AI-powered systems are transforming industries worldwide.

WEBSITE: https://www.ficusoft.in/deep-learning-training-in-chennai/

[industrynewsupdates]

Image Recognition Market Size, Share And Trends Analysis Report

The global image recognition market size is expected to reach USD 128.3 billion by 2030, registering a CAGR of 12.8% from 2024 to 2030, according to a new report by Grand View Research, Inc. Image processing and recognition have evolved with numerous powerful applications, such as security and surveillance, and medical imaging that have created a great value from a business perspective. Functions of figure identification, such as facial or object recognition, visual geolocation, barcode reading, and automated driver assistance, among other industrial automation-related functions, have demonstrated the versatility of this technology. When combined with AI, this technology has begun to create valuable growth opportunities in several verticals, such as gaming, social networking, and e-commerce. For instance, Twitter and Facebook, two major platforms in the world of social networking, have benefited from the technology in terms of audience engagement as they have created a more connected experience by encouraging users to share images and tag their friends.

The advent of digital cameras, particularly cameras built into smartphones, has led to an exponential growth in the volume of digital content in the form of images and videos. A vast amount of visual and digital data is being captured and shared through several applications, websites, social networks, and other digital channels. Several businesses have leveraged this online content to deliver better and smarter services to their customers, with the use of digital image processing. For instance, in October 2019, SnapPay Inc., a U.S. based payment platform provider, has launched facial recognition payment technology in the North America region. By using this thechnology in its payment solution, the company has aimed at allowing its customers a new level of convenience for payments at retail outlets.

Gather more insights about the market drivers, restrains and growth of the Image Recognition Market

Image Recognition Market Report Highlights

• Facial recognition dominated the market and accounted for the largest revenue share of 22.5% in 2023. The increasing demand for enhanced security measures across various industries, such as government, banking, and retail, has significantly contributed to the dominance of facial recognition systems.

• The service segment led the market and accounted for the largest revenue share of 39.1% in 2023. The service segment offers tailored image recognition solutions that can be customized to meet the specific needs of businesses across various industries.

• The cloud segment held the largest market revenue share of 71.6% in 2023. The rise in the cloud-based market is due to its greater use in industries needing centralized monitoring, such as BFSI, media, government, and entertainment.

• The retail & e-commerce segment dominated the market with a share of 21.0% in 2023. E-commerce websites prioritize content management to enhance their product offerings and boost sales.

• The marketing & advertising segment held the largest market share of 29.6% in 2023. Many businesses adopted technology with advanced advertising, customer interaction, and branding to improve their marketing activities.

• North America image recognition market dominated the global market and accounted for the largest revenue share of 34.0% in 2023. The rise in the market is due to the growing inclusion of AI and mobile computing in online shopping and e-commerce industries.

Image Recognition Market Segmentation

Grand View Research has segmented global image recognition market report based on, technique, component, deployment mode, vertical, application, and region:

Image Recognition Technique Outlook (Revenue, USD Million, 2018 - 2030)

• QR/ Barcode Recognition

• Object Recognition

• Facial Recognition

• Pattern Recognition

• Optical Character Recognition

Image Recognition Component Outlook (Revenue, USD Million, 2018 - 2030)

• Hardware

• Software

• Service

o Managed

o Professional

o Training, Support, and Maintenance

Image Recognition Deployment Mode Outlook (Revenue, USD Million, 2018 - 2030)

• Cloud

• On-Premises

Image Recognition Vertical Outlook (Revenue, USD Million, 2018 - 2030)

• Retail & E-commerce

• Media & Entertainment

• BFSI

• Automobile & Transportation

• Telecom & IT

• Government

• Healthcare

• Others

Image Recognition Application Outlook (Revenue, USD Million, 2018 - 2030)

• Augmented Reality

• Scanning & Imaging

• Security & Surveillance

• Marketing & Advertising

• Image Search

Image Recognition Regional Outlook (Revenue, USD Million, 2018 - 2030)

• North America

o U.S.

o Canada

o Mexico

• Europe

o UK

o Germany

o France

• Asia Pacific

o China

o India

o Japan

o Australia

o South Korea

• Latin America

o Brazil

• Middle East and Africa (MEA)

o Saudi Arabia

o South Africa

o UAE

Order a free sample PDF of the Image Recognition Market Intelligence Study, published by Grand View Research.

[kawaiikinghologram]

Armin Ordodary, FSM Smart, and Lau Global Services

In the era of CFDs and binary options, massive international forex operations arose. With the peak occurring in or around 2015, many of them began operating between 2010 and 2012. Legislators and regulators needed some time to recognize emerging trends and devise effective countermeasures. The beginning of 2014 saw regulators issue warnings about binary options, signaling the end of the FX gold rush. It took three more years for regulators to formally outlaw binary options. A few international forex operations impacted hundreds of thousands of retail investors between 2012 and 2017. One of the groups that created a wave of binary options, forex, and cryptocurrency trading methods is Lau Global Services Corp. Media has requested additional information to establish an EFRI funds recovery campaign.

The FSM Smart Broker Scheme by Armin Ordodary

The FSM Smart operation has been aggressively gaining clients through their Serbian boiler room Upmarket d.o.o., according to information provided to the media by whistleblowers. Benrich Holdings Ltd., a company based in Cyprus, is the only shareholder in this boiler room. Armin Ordodary, a resident of Cyprus, is a director of both companies. Upmarkt is only one of the Lau Global Services Corp operations' several boiler rooms. FinTelegrem has information that indicates FSM Smart and Armin Ordodary are involved in the “Lau Network.”

The “Lau Network” has only a few minor branches, including the Serbian Upmarkt d.o.o. Kiev, Ukraine, has served as something of an epicenter for additional boiler rooms that have already been discovered in other jurisdictions. For instance, call center addresses in Kiev were discovered by the Russian website Forex Analysis. Apart from E&G Bulgaria, Lau Global Services Corp is unquestionably one of the biggest broker enterprises on the planet. Even with so many offshore connections, this operation appears to be run out of Ukraine and the Balkans.

The Global Services Network of Lau

It is clear that there are connections between the operators of FSM Smart and other individuals, such as MTI Markets (www.mtimarkets.com). According to reports, Lau Global Services Corp., the company behind this unlawful broker, also ran the following other broker operations:

TradingMX (www.tradingmx.com)

LGS Corp www.lgs-corp.com

TradingBanks (www.tradingbanks.com)

Trade12 (https://www.trade12.com)

MTI Markets (mtimarkets.com)

Grizzly (www.grizzly-ltd.com)

The following companies have been linked to the Lau Global Services Group by the Media team:

Belize’s Lau Global Services Corp

Serbian Upmarkt d.o.o

Global Fin Services Ltd (UK), Exo Capital Markets Ltd (Marshall Islands), and MTI Investments LLC or MTI Markets Ltd (Marshall Islands)

Malta-based Grizzly Ltd

Cyprus-based R Capital Solutions Ltd

Cyprus-based Benrich Holdings Ltd

SIO Ltd (Cyprus)

Eyar Financial Corp Limited (Vanatu)

Regulators from many jurisdictions issued numerous warnings to the brands and businesses connected to Lau Global Services Corp.

August 2015: MXTrade and Lau Global Services were the targets of an investor alert by the Italian CONSOB.

September 2015: MXTrade and Lau Global Services were the targets of an investor alert from Cyprus agency CySec.

April 2016: The Belgian Financial Services Authority (FSMA) cautioned investors.

November 2016: The Australian regulator ASIC issued a warning to investors about MXTrade.

November 2016: The New Zealand regulator FMA issued a warning to investors about EXO Capital Markets Ltd. trading as Trade12.

November 2017: The Guernsey regulator issued a warning to investors about Exo Capital Markets Ltd. trading as Trade12.

Individuals Found in the Network

The individuals listed in the FSM Smart network include Mathew Bradley, Ali Mahmoudi, and Armin Ordodary, a resident of Cyprus who is purportedly a former Windsor Brokers employee. Born in January of 1991, Armin Ordodary has registered multiple forex trading domains during the years of 2013 and 2014. In addition, he serves as the director of Bythos Yachts Management OÜ in Estonia.

The well-established ties that Armin Ordodary

We are unable to determine at this time if Armin Ordodary was a lieutenant in Cyprus or one of the network’s leaders. In actuality, we have managed to determine his affiliation with businesses, endeavors, and undertakings within the brokering landscape. He has ties to both the Nepcore project and SIAO Ltd, a provider of services. Additionally, we are aware that he oversees the Upmarkt boiler room in Serbia, which provided services to FSM Smart. He offered marketing services for the Lau Network’s operations through Nepcore.

[businessindustry]

Control Room Solutions Market Report, Analysis, Size and Share by 2025-2033

The Reports and Insights, a leading market research company, has recently releases report titled “Control Room Solutions Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2025-2033.” The study provides a detailed analysis of the industry, including the global Control Room Solutions Market share, size, trends, and growth forecasts. The report also includes competitor and regional analysis and highlights the latest advancements in the market.

Report Highlights:

How big is the Control Room Solutions Market?

The global control room solution market was valued at US$ 51.7 Billion in 2024 and is expected to register a CAGR of 6.8% over the forecast period and reach US$ 93.5 Bn in 2033.

What are Control Room Solutions?

A control room solution encompasses the technologies, systems, and services designed to facilitate real-time monitoring, management, and decision-making in mission-critical environments such as security operations, transportation networks, utilities, and emergency response centers. These solutions integrate advanced visualization tools, video walls, ergonomic workstations, data aggregation software, and communication systems to provide operators with seamless access to actionable insights and centralized control. By enabling efficient collaboration, situational awareness, and rapid response, control room solutions play a pivotal role in enhancing operational efficiency, minimizing downtime, and ensuring safety and security across various industries.

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What are the growth prospects and trends in the Control Room Solutions industry?

The control room solutions market growth is driven by various factors and trends. The control room solutions market is experiencing robust growth, driven by increasing demand for advanced monitoring and management systems in industries such as transportation, energy, utilities, public safety, and defense. Key trends include the adoption of cutting-edge technologies like AI, IoT, and big data analytics to enhance situational awareness and decision-making. The growing focus on smart cities and critical infrastructure protection is fueling the need for integrated control room solutions. Additionally, advancements in visualization tools, such as high-resolution video walls and ergonomic operator interfaces, are improving efficiency and collaboration. Rising investments in digital transformation and the need for real-time, centralized control in mission-critical environments further drive market expansion. Hence, all these factors contribute to control room solutions market growth.

What is included in market segmentation?

The report has segmented the market into the following categories:

By Solution

Hardware

LCD Video Walls

LED Video Walls

Rear Projections Video Walls

Processors and Controllers

Consoles and Workstations

Communication Devices

Environmental Controls

Others

Software

Data Visualization Software

Command and Control Systems

Incident Management Software

Analytics and Reporting Tools

Others

Services

Installation and Integration

Maintenance and Support

Consulting and Training

By Deployment

On-Premise Solutions

Cloud-Based Solutions

Hybrid Solutions

By Enterprise Size

Small Enterprise

Medium Enterprise

Large Enterprises

By End-User

Government and Defense

Utilities and Energy

Transportation and Logistics

Manufacturing

Healthcare

IT & Telecommunications

Media and Entertainment

Banking and Financial Services

Hospitality

Retail Sector

Others

North America

United States

Canada

Europe

Germany

United Kingdom

France

Italy

Spain

Russia

Poland

Benelux

Nordic

Rest of Europe

Asia Pacific

China

Japan

India

South Korea

ASEAN

Australia & New Zealand

Rest of Asia Pacific

Latin America

Brazil

Mexico

Argentina

Middle East & Africa

Saudi Arabia

South Africa

United Arab Emirates

Israel

Rest of MEA

Who are the key players operating in the industry?

The report covers the major market players including:

Delta Electronics

Barco

Haivision

Mauell Corporation

Regola S.r.l.

Christie Digital Systems USA, Inc.

Mistral Solutions Pvt. Ltd.

IHM A/S

Airbus

MOTILDE

Planar Systems

RGB Spectrum

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The stock market, a cornerstone of global finance, has undergone significant transformation over the years. From human brokers shouting on the trading floor to digital transactions completed in milliseconds, the evolution has been remarkable. In recent years, artificial intelligence (AI) has taken this evolution a step further. AI's growing influence on the stock market has sparked debates about its role, efficiency, and ethical implications. But are there really bots managing trades, and how significant is their impact? The Rise of AI in Stock Market Trading AI has become an integral part of the financial industry, particularly in stock trading. High-frequency trading (HFT), powered by AI algorithms, accounts for a substantial portion of trades executed on major stock exchanges. These algorithms analyze vast datasets in real-time, identify patterns, and execute trades at lightning speed. The primary advantage is efficiency: AI can process and act on information far faster than any human. Firms like Goldman Sachs and Morgan Stanley have invested heavily in AI-driven trading systems. Hedge funds, too, are leveraging AI to predict market trends, optimize portfolios, and manage risks. AI's ability to learn and adapt has made it a game-changer in a field where split-second decisions can mean millions gained or lost. How Do AI Bots Work in Trading? AI bots operate through complex algorithms that process data, identify opportunities, and execute trades. These bots rely on machine learning models trained on historical data to predict future trends. Key components of AI trading systems include: - Data Analysis: AI bots analyze financial reports, news articles, social media sentiment, and even geopolitical events to gauge market sentiment. - Pattern Recognition: They identify recurring patterns in stock prices and use these patterns to predict future movements. - Automated Execution: Once an opportunity is identified, the bot executes trades without human intervention, ensuring speed and precision. For example, if a bot detects a sudden spike in positive sentiment about a particular company, it might buy shares before the price rises. Conversely, it can sell shares if negative sentiment emerges, minimizing potential losses. Are Bots Really Doing the Job? The short answer is yes, but their roles vary. While some bots execute trades, others provide analytical insights or assist in decision-making. Here’s how they’re involved: - High-Frequency Trading (HFT): HFT bots dominate this space, making trades within fractions of a second to capitalize on minute price differences. - Portfolio Management: Robo-advisors like Betterment and Wealthfront use AI to manage portfolios for retail investors, balancing risk and return based on individual goals. - Market Predictions: AI models like deep learning networks forecast stock prices by analyzing historical data and market trends. - Sentiment Analysis: Bots track public sentiment using natural language processing (NLP), helping traders understand how news or events might affect stock prices. Benefits of AI in Stock Trading AI's presence in the stock market brings numerous advantages: - Speed and Efficiency: AI executes trades faster than humans, often securing better prices. - Reduced Emotional Bias: Unlike humans, AI bots don’t suffer from fear or greed, leading to more rational decision-making. - 24/7 Operation: AI bots can analyze markets and execute trades around the clock, especially useful for global markets operating in different time zones. - Data-Driven Insights: AI’s ability to analyze massive datasets provides traders with actionable insights, enhancing decision-making. Challenges and Risks of AI in Stock Trading Despite its advantages, AI trading is not without challenges: - Market Volatility: High-frequency trades by AI bots can exacerbate market volatility. Flash crashes, like the one in 2010, have been partly attributed to algorithmic trading. - Lack of Transparency: Many AI models are "black boxes," meaning their decision-making processes are not easily understood. This opacity can lead to trust issues. - Ethical Concerns: The use of AI in trading raises questions about fairness. Smaller investors may struggle to compete with institutional players using advanced AI systems. - Systemic Risks: A malfunctioning algorithm could trigger massive sell-offs, causing widespread market disruption. The Future of AI in Stock Markets AI's role in the stock market is expected to grow, driven by advancements in technology and increased adoption. Key trends include: - Explainable AI: Efforts are underway to make AI models more transparent, enabling traders to understand and trust their decisions. - Integration with Blockchain: Combining AI with blockchain could enhance transparency and security in trading. - Regulation: Governments and regulatory bodies are likely to introduce stricter guidelines to ensure AI is used ethically and responsibly. - Personalized Trading: AI could offer tailored investment strategies based on individual preferences, making stock trading more accessible to retail investors. Human Traders vs. AI Bots The rise of AI in trading has sparked concerns about job displacement. While AI excels in speed and data analysis, human traders bring creativity, intuition, and a deep understanding of market psychology—qualities AI cannot replicate. Instead of replacing humans, AI is likely to complement their skills, enabling better decision-making and improved efficiency. Conclusion AI has undeniably revolutionized the stock market, with bots playing significant roles in trading and analysis. From high-frequency trading to portfolio management, their impact is profound. However, as with any technological advancement, challenges and risks must be addressed to ensure AI’s potential is fully realized. The future of stock trading lies in collaboration—a partnership where human intelligence and AI work together to navigate the complexities of the financial world. As the industry evolves, striking the right balance between innovation and regulation will be crucial to fostering a fair and efficient market for all participants. Read the full article