#api integration example

[xploreitcorp5]

How much do Java developers earn?

1. Introduction to Java Developer Salaries

What's the earning potential for Java developers? This is a hot topic for students, new grads, and folks looking to get into software development. With the growth of full stack dev, cloud tech, and enterprise software, Java remains essential. Salaries depend on location, experience, and skills. For students in Coimbatore studying Java, knowing what to expect in the industry is key. 

Key Points:

- Java developers are in demand across various fields.  

- Knowing Spring Boot and full stack skills can boost your pay.

2. Java Developer Salary for Freshers

So how much can freshers make? Entry-level Java developers in cities like Coimbatore usually earn between INR 3 to 5 LPA. Completing a Java Full Stack Developer course typically leads to better pay since it covers a wider skill set. Employers often look for hands-on experience, which is why doing Java mini projects or internships is important.  

Key Points:

- Fresh Java developers start around INR 3 LPA.  

- Getting certified in Java can help you land a job.

3. Experienced Java Developer Salaries

With 3-5 years under your belt, what can you expect? Salaries typically range from INR 6 to 12 LPA. Those who take a Java training course in Coimbatore often find they earn more. Companies want people with strong backend skills and experience with tools like Spring, Hibernate, or Microservices. 

Key Points:

- Mid-level Java developers can earn between INR 6 to 12 LPA.  

- Knowledge of Spring and REST APIs can increase your salary.

4. Senior Java Developer Salary

 InsightsFor those at a senior level with over 7 years of experience, earnings can start at INR 15 to 25 LPA. This varies based on company size and responsibilities, plus keeping up with new tech is crucial. Attending weekend Java classes or coaching sessions can help keep skills fresh.

Key Points:-

- Senior Java developers generally earn over INR 15 LPA.  

- Full stack skills can lead to higher pay.

5. Java Full Stack Developer Salaries

People who complete a Java Full Stack Developer Course in Coimbatore often snag higher-paying jobs. Full stack developers with skills in Java, React, and DevOps can earn about 20% more than those focused solely on Java. If you're curious about Java salaries, investing in full stack training is a smart move.  

Key Points:

- Full stack Java developers can earn about 20% more.  

- Having both frontend and backend knowledge is important.

6. Salary Trends in Coimbatore and Tier-2 Cities

In Coimbatore, students of Java courses often ask about earning potential. Starting salaries might be a bit lower than in metro areas, but there’s room for growth. Remote work options are now more common, allowing locals to earn metro-level salaries.  

Key Points:

- Java jobs in Coimbatore offer competitive pay.  

- Remote work opens doors to higher salaries.

7. Java Certification and Salary Growth

Getting certified can mean a 30-40% pay bump compared to non-certified peers. Following a structured Java course helps build strong skills. Recruiters appreciate learning paths and real-world experience from platforms offering Java programs.  

Key Points:

- Java certifications help boost your credibility.  

- Structured training can get you better job offers.

8. Demand for Java Developers in 2025

Looking ahead, there’s expected growth of 15% in Java jobs by 2025. More students are signing up for Java Full Stack Developer Courses in Coimbatore, and chances for freshers are expanding. Mastering Java basics through tutorials can help set you up for success.  

Key Points:

- Job openings for Java developers are on the rise.  

- Full stack training fits well with job market trends.

9. Java Developer Skills That Influence Salaries

Earnings for Java developers often depend on skills like Spring Boot, Microservices, REST APIs, and cloud integration. Regular practice with Java exercises, internships, and coaching can create a strong candidate.  

Key Points:

- Skills in demand directly impact salary.  

- Ongoing learning is vital for career growth.

10. Conclusion and Brand Mention

So how much do Java developers actually make? It varies, but with the right skills and certifications, Java can lead to a rewarding job. Whether you’re just starting out or looking to advance, getting good training is key. If you want to begin or progress in your career, check out Xplore It Corp for Java courses and training designed to help you succeed.  

Key Points:

- Look for recognized training programs.  

- Xplore It Corp can help you close skills and salary gaps.

FAQs

Q1. How much do Java developers earn after certification?

A certified Java developer can earn 30-40% more than non-certified ones.  

Q2. Are Full Stack Developer salaries higher?

Yes, full stack developers generally make 20-25% more due to their wider range of skills.  

Q3. Does location affect salaries?

Absolutely, metro cities tend to pay more, but remote jobs are helping close that gap in places like Coimbatore.  

Q4. Is a Java internship necessary?

Not strictly necessary, but internships can really enhance a resume, especially for those just starting out.  

Q5. What's the best way to learn Java step by step?

Join a structured course, like those from Xplore It Corp, and practice with Java tutorials and coding exercises.

[thedbahub]

Enhancing SQL Server with External API Calls: A Guide to sp_invoke_external_rest_endpoint

In the bustling world of database management, SQL Server shines as a beacon of strength, flexibility, and a treasure trove of features ready to tackle a wide array of data challenges. Among its many jewels is a feature that feels almost like magic: the ability to chat with external APIs right from the cozy confines of T-SQL code, courtesy of the sp_invoke_external_rest_endpoint stored procedure.…

[literaryvein-reblogs]

Writing Notes: Source Integration for Historical Writing

When writing for history courses, it is common to incorporate evidence from primary and secondary sources.

Writers integrate information from these sources into their writing in 3 ways:

Summaries

Writers typically summarize when the information from a source does not have to be provided in detail.

For example, a writer might want to summarize an author’s overall argument for the audience as opposed to explaining every line.

Summaries are particularly useful for describing key historical events or figures.

Writers can use descriptive facts, such as names, dates, and places, to create a summary that provides critical background information for the audience.

Example

In Kris Myers’ (2012, 198) essay, she traces the development of the Alice Paul Institute (API), also known as Paulsdale, a house museum that features historical lessons based on the life of women’s rights activist Alice Paul.

Paraphrases

Paraphrasing works best when writers can state information from a source in a more clear and concise manner without changing the original meaning of the words. Under most circumstances, readers expect to see paraphrased evidence in historical writing. Paraphrasing helps writers balance information from their sources with their own words and voice.

For example, if a writer wants to include an author’s idea to support their argument, but the original text spans an entire paragraph, the writer can paraphrase key details from the original paragraph into one or two sentences to capture the important aspects.

Example

Myers (2012, 198) states the API decided to use Alice Paul’s life as the foundation for a leadership program that teaches young girls skills to become leaders in their community.

Quotations

Quotations suit several purposes in writing.

The most common reasons writers use quotations are when the words serve as concrete evidence to back up a claim, come from an authoritative figure that adds credibility to their argument, are so compelling and original that there is no better way to express the idea, or communicate an idea in order to accurately dispute it.

For historical writing, quotations are used to reference primary and secondary sources as evidence to support an argument. However, writers should keep in mind that quotations from a primary source are often considered stronger forms of evidence than quotations from a secondary source.

Example

Despite the success of Paulsdale, Myers (2012, 207) notes that “[t]he API confronted constant claims that women’s history is not significant to American memory, or that women like Alice Paul represented a radical element” when advocating for the project.

Note: Always refer to assignment instructions for specific information regarding which citation style to use and how many sources or quotations are required.

Source ⚜ More: Writing Notes & References

[goblin-social]

A quick example of the current state of Goblin:

I imported my following list from mastodon and started following everyone with my goblin.band account too, so I basically read all my mastodon content from there already. Even if no one but me using the tumblr-like features I'm adding, I already enjoy Goblin more than Mastodon.

Things that I've added since my last post:

Integration with mastodon (and well, any other fediverse platform that use plain text instead of html)

Copy/pasting images in the editor

Sanitized html input when saving & updating posts

Improved the landing page

Cleaned the menus and improved the UI in general

Current "next" to-do list:

Fix posts displaying images twice when you paste an image

Fix RSS feed including the inline files again after the post

Sanitize html inputs on incoming federated posts

fix several style issues around different settings sections (black texts on dark blue background, white text over white background, etc)

Figure out if I can create a tumblr-api app so the posts from goblin can be automatically shared here without having to go through Zappier.

Figure out what kind of server I need to run a, let's say, 500 people server.

Find someone to do some security review of my server (Long story short, I've only a very slim idea of what I'm doing when configuring a server and I'm sure I've left some huge security holes around).

This is happening, folks. I think Goblin is going to be a reality. At least https://goblin.band will be.

[acuvate-updates]

How Agentic AI & RAG Revolutionize Autonomous Decision-Making

In the swiftly advancing realm of artificial intelligence, the integration of Agentic AI and Retrieval-Augmented Generation (RAG) is revolutionizing autonomous decision-making across various sectors. Agentic AI endows systems with the ability to operate independently, while RAG enhances these systems by incorporating real-time data retrieval, leading to more informed and adaptable decisions. This article delves into the synergistic relationship between Agentic AI and RAG, exploring their combined impact on autonomous decision-making.

Overview

Agentic AI refers to AI systems capable of autonomous operation, making decisions based on environmental inputs and predefined goals without continuous human oversight. These systems utilize advanced machine learning and natural language processing techniques to emulate human-like decision-making processes. Retrieval-Augmented Generation (RAG), on the other hand, merges generative AI models with information retrieval capabilities, enabling access to and incorporation of external data in real-time. This integration allows AI systems to leverage both internal knowledge and external data sources, resulting in more accurate and contextually relevant decisions.

Read more about Agentic AI in Manufacturing: Use Cases & Key Benefits

What is Agentic AI and RAG?

Agentic AI: This form of artificial intelligence empowers systems to achieve specific objectives with minimal supervision. It comprises AI agents—machine learning models that replicate human decision-making to address problems in real-time. Agentic AI exhibits autonomy, goal-oriented behavior, and adaptability, enabling independent and purposeful actions.

Retrieval-Augmented Generation (RAG): RAG is an AI methodology that integrates a generative AI model with an external knowledge base. It dynamically retrieves current information from sources like APIs or databases, allowing AI models to generate contextually accurate and pertinent responses without necessitating extensive fine-tuning.

Know more on Why Businesses Are Embracing RAG for Smarter AI

Capabilities

When combined, Agentic AI and RAG offer several key capabilities:

Autonomous Decision-Making: Agentic AI can independently analyze complex scenarios and select effective actions based on real-time data and predefined objectives.

Contextual Understanding: It interprets situations dynamically, adapting actions based on evolving goals and real-time inputs.

Integration with External Data: RAG enables Agentic AI to access external databases, ensuring decisions are based on the most current and relevant information available.

Enhanced Accuracy: By incorporating external data, RAG helps Agentic AI systems avoid relying solely on internal models, which may be outdated or incomplete.

How Agentic AI and RAG Work Together

The integration of Agentic AI and RAG creates a robust system capable of autonomous decision-making with real-time adaptability:

Dynamic Perception: Agentic AI utilizes RAG to retrieve up-to-date information from external sources, enhancing its perception capabilities. For instance, an Agentic AI tasked with financial analysis can use RAG to access real-time stock market data.

Enhanced Reasoning: RAG augments the reasoning process by providing external context that complements the AI's internal knowledge. This enables Agentic AI to make better-informed decisions, such as recommending personalized solutions in customer service scenarios.

Autonomous Execution: The combined system can autonomously execute tasks based on retrieved data. For example, an Agentic AI chatbot enhanced with RAG can not only answer questions but also initiate actions like placing orders or scheduling appointments.

Continuous Learning: Feedback from executed tasks helps refine both the agent's decision-making process and RAG's retrieval mechanisms, ensuring the system becomes more accurate and efficient over time.

Read more about Multi-Meta-RAG: Enhancing RAG for Complex Multi-Hop Queries

Example Use Case: Customer Service

Customer Support Automation Scenario: A user inquiries about their account balance via a chatbot.

How It Works: The Agentic AI interprets the query, determines that external data is required, and employs RAG to retrieve real-time account information from a database. The enriched prompt allows the chatbot to provide an accurate response while suggesting payment options. If prompted, it can autonomously complete the transaction.

Benefits: Faster query resolution, personalized responses, and reduced need for human intervention.

Example: Acuvate's implementation of Agentic AI demonstrates how autonomous decision-making and real-time data integration can enhance customer service experiences.

2. Sales Assistance

Scenario: A sales representative needs to create a custom quote for a client.

How It Works: Agentic RAG retrieves pricing data, templates, and CRM details. It autonomously drafts a quote, applies discounts as instructed, and adjusts fields like baseline costs using the latest price book.

Benefits: Automates multi-step processes, reduces errors, and accelerates deal closures.

3. Healthcare Diagnostics

Scenario: A doctor seeks assistance in diagnosing a rare medical condition.

How It Works: Agentic AI uses RAG to retrieve relevant medical literature, clinical trial data, and patient history. It synthesizes this information to suggest potential diagnoses and treatment options.

Benefits: Enhances diagnostic accuracy, saves time, and provides evidence-based recommendations.

Example: Xenonstack highlights healthcare as a major application area for agentic AI systems in diagnosis and treatment planning.

4. Market Research and Consumer Insights

Scenario: A business wants to identify emerging market trends.

How It Works: Agentic RAG analyzes consumer data from multiple sources, retrieves relevant insights, and generates predictive analytics reports. It also gathers customer feedback from surveys or social media.

Benefits: Improves strategic decision-making with real-time intelligence.

Example: Companies use Agentic RAG for trend analysis and predictive analytics to optimize marketing strategies.

5. Supply Chain Optimization

Scenario: A logistics manager needs to predict demand fluctuations during peak seasons.

How It Works: The system retrieves historical sales data, current market trends, and weather forecasts using RAG. Agentic AI then predicts demand patterns and suggests inventory adjustments in real-time.

Benefits: Prevents stockouts or overstocking, reduces costs, and improves efficiency.

Example: Acuvate’s supply chain solutions leverage predictive analytics powered by Agentic AI to enhance logistics operations

How Acuvate Can Help

Acuvate specializes in implementing Agentic AI and RAG technologies to transform business operations. By integrating these advanced AI solutions, Acuvate enables organizations to enhance autonomous decision-making, improve customer experiences, and optimize operational efficiency. Their expertise in deploying AI-driven systems ensures that businesses can effectively leverage real-time data and intelligent automation to stay competitive in a rapidly evolving market.

Future Scope

The future of Agentic AI and RAG involves the development of multi-agent systems where multiple AI agents collaborate to tackle complex tasks. Continuous improvement and governance will be crucial, with ongoing updates and audits necessary to maintain safety and accountability. As technology advances, these systems are expected to become more pervasive across industries, transforming business processes and customer interactions.

In conclusion, the convergence of Agentic AI and RAG represents a significant advancement in autonomous decision-making. By combining autonomous agents with real-time data retrieval, organizations can achieve greater efficiency, accuracy, and adaptability in their operations. As these technologies continue to evolve, their impact across various sectors is poised to expand, ushering in a new era of intelligent automation.

[voiceapisolutions]

How Enterprises Use Voice APIs for Call Routing and IVR Automation

Enterprises today handle thousands of customer calls every day. To manage these efficiently, many are turning to voice APIs. These tools help businesses automate call routing and interactive voice response (IVR) systems.

What Are Voice APIs?

Voice APIs are software interfaces that allow developers to build voice-calling features into apps or systems. These APIs can trigger actions like placing calls, receiving them, or converting speech to text. For enterprises, voice APIs make it easy to integrate intelligent call handling into their workflow.

Smarter Call Routing

Call routing directs incoming calls to the right agent or department. With voice APIs, this process becomes dynamic and rules based.

For example, a customer calling from a VIP number can be routed directly to a premium support team. APIs allow routing rules based on caller ID, time of day, location, or even previous interactions. This reduces wait times and improves customer satisfaction.

Automated IVR Systems

Interactive Voice Response (IVR) lets callers interact with a menu system using voice or keypad inputs. Traditional IVR systems are rigid and often frustrating.

Voice APIs enable smarter, more personalized IVR flows. Enterprises can design menus that adapt in real time. For instance, returning callers may hear different options based on their past issues. With speech recognition, users can speak naturally instead of pressing buttons.

Scalability and Flexibility

One major benefit of using voice API is scalability. Enterprises don’t need physical infrastructure to manage call volume. The cloud-based nature of voice APIs means businesses can handle spikes in calls without losing quality.

Also, changes to call flows can be made quickly. New routing rules or IVR scripts can be deployed without touching hardware. This agility is crucial in fast-moving industries.

Enhanced Analytics and Integration

Voice APIs also provide detailed data. Enterprises can track call duration, drop rates, wait times, and common IVR paths. This data helps optimize performance and identify pain points.

Moreover, APIs easily integrate with CRMs, ticketing systems, and analytics tools. This ensures a seamless connection between calls and other business processes.

Final Thoughts

Voice APIs are transforming how enterprises manage voice communications. From intelligent call routing to adaptive IVR systems, the benefits are clear. Enterprises that adopt these tools gain speed, efficiency, and better customer experience, and that too without a lot of effort.

[allthebrazilianpolitics]

Fully protected marine areas in Brazil are contaminated by microplastics

Researchers from the Federal University of São Paulo used oysters and mussels as sentinel organisms to assess the presence of these pollutants. The results show that even the most restrictive sites for human presence have significant contamination.

Despite being considered sanctuaries for biodiversity, Brazil’s marine protected areas (MPAs) are not immune to microplastic contamination. A recent study has shown that even MPAs classified as integral protection areas (APIs), which are the most restrictive to human intervention, are contaminated by this material. The research, which involved Brazilian and Australian scientists, used bivalve mollusks (oysters and mussels) as sentinel organisms to assess contamination. The results were published in the journal Environmental Research.

“Our study showed that microplastic contamination occurs even in the most restrictive environmental protection areas. For example, in Atol das Rocas, where there’s no economic activity and tourists aren’t allowed to visit. Microplastics can reach places like this by being carried by the wind or ocean currents,” Ítalo Braga, coordinator of the research funded by FAPESP and professor at the Institute of Marine Science of the Federal University of São Paulo (IMar-UNIFESP) in Brazil, told Agência FAPESP. 

Microplastics are particles ranging in size from 1 micron (1 μm) to 5 millimeters (5 mm) that result from the fragmentation of larger plastics or are directly manufactured in this format for industrial or cosmetic use. Those detected in the study showed consistent patterns along the Brazilian coast: predominantly black, white or transparent, and less than 1 millimeter in size.

Continue reading.

[allaboutkeyingo]

What's the difference between Microsoft Office 2021 and 2024

Here are the main differences between Microsoft Office 2021 and Office 2024:

Feature Enhancements

• AI Integration: Office 2024 incorporates AI-enabled features across all core applications. For example, Word offers improved grammar suggestions and stylistic advice, Excel provides enhanced data analysis capabilities, and PowerPoint includes automatic slide suggestions, Which are not available in Office 2021.

• Collaboration Tools: Office 2024 has better real-time co-authoring and cloud integration through OneDrive and SharePoint. It also has more seamless connections with Microsoft Teams, allowing for smoother file synchronization and real-time collaboration.

• New Data Analysis Tools: Excel in Office 2024 has more advanced data analysis functionalities compared to Office 2021.

• Presentation Enhancements: PowerPoint in Office 2024 has new tools for interactive presentations and improved multimedia support.

• Integration and Compatibility： Cloud Integration: Office 2024 has a more robust and seamless integration with Microsoft’s cloud ecosystem. It supports newer technologies and APIs, making it easier to integrate with third-party applications such as project management tools and CRM systems. ODF Format Support: Office 2024 supports ODF 1.4, while Office 2021 supports ODF 1.3.

• System Requirements: RAM Requirements: Office 2024 requires at least 8 GB of RAM, while Office 2021 requires 4 GB.

• Other Differences: Microsoft Publisher: Office 2024 does not include Microsoft Publisher, while Office 2021 does. Support Lifecycle: Office 2021 has a 5-year support lifecycle with extended support options, while Office 2024 has a 5-year support lifecycle without extended support.

• Price (only at keyingo.com) Office 2021 Professional Plus is $59.99  Office 2021 Home Busienss for Mac $59.98 Office 2024 Home Business is $129.99  Office 2024 Professional Plus LTSC 500 Users $1299.99 Office 2024 Standard LTSC 500 Users $799.99

[govindhtech]

Google Cloud’s BigQuery Autonomous Data To AI Platform

BigQuery automates data analysis, transformation, and insight generation using AI. AI and natural language interaction simplify difficult operations.

The fast-paced world needs data access and a real-time data activation flywheel. Artificial intelligence that integrates directly into the data environment and works with intelligent agents is emerging. These catalysts open doors and enable self-directed, rapid action, which is vital for success. This flywheel uses Google's Data & AI Cloud to activate data in real time. BigQuery has five times more organisations than the two leading cloud providers that just offer data science and data warehousing solutions due to this emphasis.

Examples of top companies:

With BigQuery, Radisson Hotel Group enhanced campaign productivity by 50% and revenue by over 20% by fine-tuning the Gemini model.

By connecting over 170 data sources with BigQuery, Gordon Food Service established a scalable, modern, AI-ready data architecture. This improved real-time response to critical business demands, enabled complete analytics, boosted client usage of their ordering systems, and offered staff rapid insights while cutting costs and boosting market share.

J.B. Hunt is revolutionising logistics for shippers and carriers by integrating Databricks into BigQuery.

General Mills saves over $100 million using BigQuery and Vertex AI to give workers secure access to LLMs for structured and unstructured data searches.

Google Cloud is unveiling many new features with its autonomous data to AI platform powered by BigQuery and Looker, a unified, trustworthy, and conversational BI platform:

New assistive and agentic experiences based on your trusted data and available through BigQuery and Looker will make data scientists, data engineers, analysts, and business users' jobs simpler and faster.

Advanced analytics and data science acceleration: Along with seamless integration with real-time and open-source technologies, BigQuery AI-assisted notebooks improve data science workflows and BigQuery AI Query Engine provides fresh insights.

Autonomous data foundation: BigQuery can collect, manage, and orchestrate any data with its new autonomous features, which include native support for unstructured data processing and open data formats like Iceberg.

Look at each change in detail.

User-specific agents

It believes everyone should have AI. BigQuery and Looker made AI-powered helpful experiences generally available, but Google Cloud now offers specialised agents for all data chores, such as:

Data engineering agents integrated with BigQuery pipelines help create data pipelines, convert and enhance data, discover anomalies, and automate metadata development. These agents provide trustworthy data and replace time-consuming and repetitive tasks, enhancing data team productivity. Data engineers traditionally spend hours cleaning, processing, and confirming data.

The data science agent in Google's Colab notebook enables model development at every step. Scalable training, intelligent model selection, automated feature engineering, and faster iteration are possible. This agent lets data science teams focus on complex methods rather than data and infrastructure.

Looker conversational analytics lets everyone utilise natural language with data. Expanded capabilities provided with DeepMind let all users understand the agent's actions and easily resolve misconceptions by undertaking advanced analysis and explaining its logic. Looker's semantic layer boosts accuracy by two-thirds. The agent understands business language like “revenue” and “segments” and can compute metrics in real time, ensuring trustworthy, accurate, and relevant results. An API for conversational analytics is also being introduced to help developers integrate it into processes and apps.

In the BigQuery autonomous data to AI platform, Google Cloud introduced the BigQuery knowledge engine to power assistive and agentic experiences. It models data associations, suggests business vocabulary words, and creates metadata instantaneously using Gemini's table descriptions, query histories, and schema connections. This knowledge engine grounds AI and agents in business context, enabling semantic search across BigQuery and AI-powered data insights.

All customers may access Gemini-powered agentic and assistive experiences in BigQuery and Looker without add-ons in the existing price model tiers!

Accelerating data science and advanced analytics

BigQuery autonomous data to AI platform is revolutionising data science and analytics by enabling new AI-driven data science experiences and engines to manage complex data and provide real-time analytics.

First, AI improves BigQuery notebooks. It adds intelligent SQL cells to your notebook that can merge data sources, comprehend data context, and make code-writing suggestions. It also uses native exploratory analysis and visualisation capabilities for data exploration and peer collaboration. Data scientists can also schedule analyses and update insights. Google Cloud also lets you construct laptop-driven, dynamic, user-friendly, interactive data apps to share insights across the organisation.

This enhanced notebook experience is complemented by the BigQuery AI query engine for AI-driven analytics. This engine lets data scientists easily manage organised and unstructured data and add real-world context—not simply retrieve it. BigQuery AI co-processes SQL and Gemini, adding runtime verbal comprehension, reasoning skills, and real-world knowledge. Their new engine processes unstructured photographs and matches them to your product catalogue. This engine supports several use cases, including model enhancement, sophisticated segmentation, and new insights.

Additionally, it provides users with the most cloud-optimized open-source environment. Google Cloud for Apache Kafka enables real-time data pipelines for event sourcing, model scoring, communications, and analytics in BigQuery for serverless Apache Spark execution. Customers have almost doubled their serverless Spark use in the last year, and Google Cloud has upgraded this engine to handle data 2.7 times faster.

BigQuery lets data scientists utilise SQL, Spark, or foundation models on Google's serverless and scalable architecture to innovate faster without the challenges of traditional infrastructure.

An independent data foundation throughout data lifetime

An independent data foundation created for modern data complexity supports its advanced analytics engines and specialised agents. BigQuery is transforming the environment by making unstructured data first-class citizens. New platform features, such as orchestration for a variety of data workloads, autonomous and invisible governance, and open formats for flexibility, ensure that your data is always ready for data science or artificial intelligence issues. It does this while giving the best cost and decreasing operational overhead.

For many companies, unstructured data is their biggest untapped potential. Even while structured data provides analytical avenues, unique ideas in text, audio, video, and photographs are often underutilised and discovered in siloed systems. BigQuery instantly tackles this issue by making unstructured data a first-class citizen using multimodal tables (preview), which integrate structured data with rich, complex data types for unified querying and storage.

Google Cloud's expanded BigQuery governance enables data stewards and professionals a single perspective to manage discovery, classification, curation, quality, usage, and sharing, including automatic cataloguing and metadata production, to efficiently manage this large data estate. BigQuery continuous queries use SQL to analyse and act on streaming data regardless of format, ensuring timely insights from all your data streams.

Customers utilise Google's AI models in BigQuery for multimodal analysis 16 times more than last year, driven by advanced support for structured and unstructured multimodal data. BigQuery with Vertex AI are 8–16 times cheaper than independent data warehouse and AI solutions.

Google Cloud maintains open ecology. BigQuery tables for Apache Iceberg combine BigQuery's performance and integrated capabilities with the flexibility of an open data lakehouse to link Iceberg data to SQL, Spark, AI, and third-party engines in an open and interoperable fashion. This service provides adaptive and autonomous table management, high-performance streaming, auto-AI-generated insights, practically infinite serverless scalability, and improved governance. Cloud storage enables fail-safe features and centralised fine-grained access control management in their managed solution.

Finaly, AI platform autonomous data optimises. Scaling resources, managing workloads, and ensuring cost-effectiveness are its competencies. The new BigQuery spend commit unifies spending throughout BigQuery platform and allows flexibility in shifting spend across streaming, governance, data processing engines, and more, making purchase easier.

Start your data and AI adventure with BigQuery data migration. Google Cloud wants to know how you innovate with data.

[orsinium]

anyway that last post abt doing anything i want forever was about bug people that's right it's BEE TIME "what's their connection to the lore" absolutely nothing i made it up and im having a great time <3

Ashlo, known as the Bee God of Honeyed Reflections, the Architect of the Soul, the Ever-Attendant Queen, the Prince of All Suns, and the God of Rebirth, is an obscure and little-known national deity worshipped by the Apis peoples of Lower Craglorn. Traditional Apis belief holds that Ashlo creates the souls of all living beings by filling the honeycombs of the Golden Hive with soul honey, the basis of all life, and allowing them to grow to completion. After death, Ashlo ferries these souls back to the hive, where they will be reused for future generations. Perhaps indicative of their close contact with the Nedes, astrology and star-worship is central to Apis religion, with each star representing one cell in the Golden Hive, and each of the constellations being comprised of ancestral heroes whose souls were deemed holy enough to preserve from the cycle of rebirth so that they may watch over the living.

In at least one Iron Orc tribe there are written records of Ashlo being viewed as a minor spirit responsible for maintaining the structural integrity of religious institutions. In a less accepting example of cross-cultural exchange, the invading Ra Gada of the 1st Era associated Ashlo with Peryite, and considered them and their followers “a pestilence given form.”

The Ayleids had a scientific interest in Ashlo as a potential god of light and the dawn, but interacted little else with the Apis, and generally not in a religious capacity.

Experts connect Ashlo to Lorkhan as a creator deity, and even to the mysterious insect god of the famed Adabal-a, but no concrete evidence has swayed popular opinion either way.

[mofeoluwa]

How I Earn Passively on STON.fi Without Stress

DeFi offers endless ways to earn, but most people either complicate the process or think it’s only for expert traders. The truth? You don’t need to spend hours monitoring charts or making risky trades.

For me, STON.fi has been a game-changer. It’s simple, effective, and allows me to earn without constant effort. Here’s exactly how I do it:

✅ Providing liquidity and earning fees

✅ Staking STON tokens for exclusive rewards

✅ Farming with high-yield pools

✅ Participating in STON.fi contests for extra earnings

Let’s break it down.

1️⃣ Passive Income from Liquidity Pools

One of the easiest ways to earn on STON.fi is by providing liquidity. Instead of letting my tokens sit idle, I deposit them into a liquidity pool and get rewarded for every trade that happens in that pool.

What makes it profitable

STON token rewards: STON.fi distributes STON tokens to liquidity providers.

Loss protection: STON.fi offers a 5.72% offset, reducing potential impermanent loss.

Auto-rewards: No manual claims—everything is credited directly.

Protection fund: A $10,000 monthly budget helps secure liquidity providers.

This method requires zero daily effort. I deposit my funds and let them generate earnings while I focus on other things.

2️⃣ Staking STON for Long-Term Benefits

Staking is another effortless way I earn on STON.fi, but it’s more than just locking up tokens for APY. STON staking unlocks extra benefits that go beyond simple rewards.

Here’s what I gain from staking STON:

🔹 ARKENSTON NFT – A non-transferable NFT that grants exclusive access to STON.fi’s future governance system.

🔹 GEMSTON tokens – A community-powered token tied to the platform’s ecosystem.

Instead of just staking for yield, I gain access to the STON.fi ecosystem’s premium features.

3️⃣ Earning More with High-Yield Farming

For even higher returns, I take advantage of STON.fi’s farming pools. This is where rewards get serious.

How it works:

Provide liquidity to a farming pair

Receive LP tokens

Stake LP tokens in the farm

Earn passive rewards every few seconds

Top farms with massive APRs:

🔥 POE/TON → Over 999% APR

🔥 TADA/TON → 585% APR

🔥 WOOF/TON → 337% APR

The STON/USDT farming pool is also a solid option, recently boosted with an additional 10,000 STON (~$35,000) in rewards. Unlike other platforms, STON.fi farming has no lock-up period, meaning I can withdraw anytime.

4️⃣ Extra Earnings from STON.fi Contests

Aside from liquidity provision, staking, and farming, STON.fi offers frequent contests where I can earn rewards without investing money.

A recent example is the Infographics Contest, which had a $1,500 prize pool. These contests are perfect for community members who create content, design graphics, or actively engage with the platform.

If you’re looking for a way to earn without risking capital, these competitions provide free STON rewards just for participating.

Why STON.fi is My Go-To for Passive Income

Earning on STON.fi is straightforward and low-risk. I don’t have to trade aggressively or watch price charts all day.

✅ Providing liquidity gives me steady rewards while supporting the platform’s ecosystem.

✅ Staking STON secures future perks and governance access.

✅ Farming generates high APR returns with flexible withdrawals.

✅ Contests offer easy opportunities to earn STON without financial risk.

By combining all these methods, I’ve built a sustainable income stream without stress.

[sokowachi]

How I Earn Consistently from STON.fi Without Stress

Earning in DeFi doesn’t have to be complicated. Many people assume it requires active trading or constant monitoring of charts, but that’s far from the truth. Over time, I’ve built a steady and sustainable income stream on STON.fi without spending hours glued to my screen.

Here’s exactly how I do it:

✅ Providing liquidity and earning rewards

✅ Staking STON tokens for exclusive benefits

✅ Farming for high-yield rewards

✅ Winning STON.fi contests for extra income

Each of these methods has its own advantages, and when combined, they create a solid passive income strategy.

1️⃣ Earning Through Liquidity Provision

One of the easiest ways to generate income on STON.fi is by providing liquidity. Instead of holding tokens passively, I put them to work in the STON/USDT V2 liquidity pool and earn rewards over time.

What makes it worth it

🔹 STON rewards: 1,478 STON tokens distributed to LPs (January payout).

🔹 Impermanent loss protection: Up to 5.72% offset to minimize potential losses.

🔹 Automatic rewards: No need to manually claim—everything is credited automatically.

🔹 Protection budget: $10,000 allocated monthly to safeguard liquidity providers.

Providing liquidity isn’t just about rewards—it also helps stabilize the market by ensuring smooth transactions for traders.

2️⃣ Staking STON for Extra Benefits

Staking is another effortless way I earn from STON.fi. But unlike standard staking models that only offer yield, STON staking comes with additional advantages.

Here’s what I gain:

🔹 ARKENSTON NFT – A soulbound NFT permanently linked to my wallet. This will serve as an exclusive membership pass for STON.fi’s upcoming DAO governance system.

🔹 GEMSTON token – A community-driven token distributed upon staking, with future value tied to STON.fi’s ecosystem.

Instead of simply earning APY on my staked tokens, I also get governance rights and early access to upcoming features.

3️⃣ Farming for High-Yield Rewards

For even greater returns, I participate in farming on STON.fi. This method allows me to earn additional rewards on top of my liquidity provision.

How does it work

🔹 Add liquidity to a farming pair.

🔹 Receive LP tokens automatically.

🔹 Stake LP tokens in the farm.

🔹 Earn rewards in real-time, every few seconds.

Current high-APR farms on STON.fi:

🔥 POE/TON → Over 999% APR

🔥 TADA/TON → 585% APR

🔥 WOOF/TON → 337% APR

STON/USDT farming has also been extended and boosted, with an extra 10,000 STON (~$35,000) in rewards. Unlike other platforms, STON.fi farming has no LP token lock-up, which makes it more flexible.

4️⃣ Earning from STON.fi Contests

Beyond liquidity provision, staking, and farming, STON.fi offers frequent contests that allow users to earn extra STON rewards.

A great example is the Infographics Contest, which recently had a $1,500 prize pool. These contests reward community engagement, making it possible to earn without financial investment.

For content creators, designers, and community builders, these competitions are an easy way to stack STON tokens without market risks.

Final Thoughts

The best part about earning on STON.fi is the simplicity. There’s no need for advanced trading strategies or market timing—just smart allocation of assets into passive income streams.

🔹 Liquidity provision gives steady returns with built-in loss protection.

🔹 Staking STON provides access to exclusive perks and future governance.

🔹 Farming tokens maximizes returns with high APRs.

🔹 Community contests offer extra earning opportunities.

By combining these methods, I’ve built a reliable income stream without the stress of day trading.

[riazhatvi]

People Think It’s Fake" | DeepSeek vs ChatGPT: The Ultimate 2024 Comparison (SEO-Optimized Guide)

The AI wars are heating up, and two giants—DeepSeek and ChatGPT—are battling for dominance. But why do so many users call DeepSeek "fake" while praising ChatGPT? Is it a myth, or is there truth to the claims? In this deep dive, we’ll uncover the facts, debunk myths, and reveal which AI truly reigns supreme. Plus, learn pro SEO tips to help this article outrank competitors on Google!

Chapters

00:00 Introduction - DeepSeek: China’s New AI Innovation

00:15 What is DeepSeek?

00:30 DeepSeek’s Impressive Statistics

00:50 Comparison: DeepSeek vs GPT-4

01:10 Technology Behind DeepSeek

01:30 Impact on AI, Finance, and Trading

01:50 DeepSeek’s Effect on Bitcoin & Trading

02:10 Future of AI with DeepSeek

02:25 Conclusion - The Future is Here!

Why Do People Call DeepSeek "Fake"? (The Truth Revealed)

The Language Barrier Myth

DeepSeek is trained primarily on Chinese-language data, leading to awkward English responses.

Example: A user asked, "Write a poem about New York," and DeepSeek referenced skyscrapers as "giant bamboo shoots."

SEO Keyword: "DeepSeek English accuracy."

Cultural Misunderstandings

DeepSeek’s humor, idioms, and examples cater to Chinese audiences. Global users find this confusing.

ChatGPT, trained on Western data, feels more "relatable" to English speakers.

Lack of Transparency

Unlike OpenAI’s detailed GPT-4 technical report, DeepSeek’s training data and ethics are shrouded in secrecy.

LSI Keyword: "DeepSeek data sources."

Viral "Fail" Videos

TikTok clips show DeepSeek claiming "The Earth is flat" or "Elon Musk invented Bitcoin." Most are outdated or edited—ChatGPT made similar errors in 2022!

DeepSeek vs ChatGPT: The Ultimate 2024 Comparison

1. Language & Creativity

ChatGPT: Wins for English content (blogs, scripts, code).

Strengths: Natural flow, humor, and cultural nuance.

Weakness: Overly cautious (e.g., refuses to write "controversial" topics).

DeepSeek: Best for Chinese markets (e.g., Baidu SEO, WeChat posts).

Strengths: Slang, idioms, and local trends.

Weakness: Struggles with Western metaphors.

SEO Tip: Use keywords like "Best AI for Chinese content" or "DeepSeek Baidu SEO."

2. Technical Abilities

Coding:

ChatGPT: Solves Python/JavaScript errors, writes clean code.

DeepSeek: Better at Alibaba Cloud APIs and Chinese frameworks.

Data Analysis:

Both handle spreadsheets, but DeepSeek integrates with Tencent Docs.

3. Pricing & Accessibility

FeatureDeepSeekChatGPTFree TierUnlimited basic queriesGPT-3.5 onlyPro Plan$10/month (advanced Chinese tools)$20/month (GPT-4 + plugins)APIsCheaper for bulk Chinese tasksGlobal enterprise support

SEO Keyword: "DeepSeek pricing 2024."

Debunking the "Fake AI" Myth: 3 Case Studies

Case Study 1: A Shanghai e-commerce firm used DeepSeek to automate customer service on Taobao, cutting response time by 50%.

Case Study 2: A U.S. blogger called DeepSeek "fake" after it wrote a Chinese-style poem about pizza—but it went viral in Asia!

Case Study 3: ChatGPT falsely claimed "Google acquired OpenAI in 2023," proving all AI makes mistakes.

How to Choose: DeepSeek or ChatGPT?

Pick ChatGPT if:

You need English content, coding help, or global trends.

You value brand recognition and transparency.

Pick DeepSeek if:

You target Chinese audiences or need cost-effective APIs.

You work with platforms like WeChat, Douyin, or Alibaba.

LSI Keyword: "DeepSeek for Chinese marketing."

SEO-Optimized FAQs (Voice Search Ready!)

"Is DeepSeek a scam?" No! It’s a legitimate AI optimized for Chinese-language tasks.

"Can DeepSeek replace ChatGPT?" For Chinese users, yes. For global content, stick with ChatGPT.

"Why does DeepSeek give weird answers?" Cultural gaps and training focus. Use it for specific niches, not general queries.

"Is DeepSeek safe to use?" Yes, but avoid sensitive topics—it follows China’s internet regulations.

Pro Tips to Boost Your Google Ranking

Sprinkle Keywords Naturally: Use "DeepSeek vs ChatGPT" 4–6 times.

Internal Linking: Link to related posts (e.g., "How to Use ChatGPT for SEO").

External Links: Cite authoritative sources (OpenAI’s blog, DeepSeek’s whitepapers).

Mobile Optimization: 60% of users read via phone—use short paragraphs.

Engagement Hooks: Ask readers to comment (e.g., "Which AI do you trust?").

Final Verdict: Why DeepSeek Isn’t Fake (But ChatGPT Isn’t Perfect)

The "fake" label stems from cultural bias and misinformation. DeepSeek is a powerhouse in its niche, while ChatGPT rules Western markets. For SEO success:

Target long-tail keywords like "Is DeepSeek good for Chinese SEO?"

Use schema markup for FAQs and comparisons.

Update content quarterly to stay ahead of AI updates.

🚀 Ready to Dominate Google? Share this article, leave a comment, and watch it climb to #1!

Follow for more AI vs AI battles—because in 2024, knowledge is power! 🔍

[gloriatq1223]

Best Platforms to Trade for Forex in 2025

Forex trading continues to captivate traders worldwide, offering a dynamic and lucrative avenue for financial growth. In 2025, identifying the best platforms to trade for forex has become more crucial than ever, as technology and market demands evolve. From user-friendly interfaces to advanced tools for technical analysis, these platforms are tailored to meet the needs of both novice and seasoned traders. Whether you're diving into major currency pairs, exploring exotic options, or utilizing automated trading strategies, choosing the right platform is the foundation for success.

Core Features of Top Forex Trading Platforms

Forex trading platforms in 2025 must combine advanced functionality with accessibility to meet diverse trader needs. The following core features highlight what distinguishes the best platforms.

User-Friendly Interface

A user-friendly interface enhances efficiency and reduces errors, especially for beginners. Key features include:

Intuitive navigation for rapid trade execution.

Customizable layouts to match user preferences.

Comprehensive tutorials for ease of onboarding.

Efficient design with minimal lag, even during high volatility.

Example Platforms: MetaTrader 4 (MT4) and MetaTrader 5 (MT5) are renowned for streamlined interfaces designed to accommodate traders at all levels.

Comprehensive Charting Tools

Forex trading requires precision, and advanced charting tools are critical for analysis. The following charting tools enhance strategy formulation:

Drawing Tools: Support for trendlines and channels.

Indicators: Integration of MACD, RSI, Bollinger Bands, and Fibonacci Retracement.

Timeframes: Options to analyze data across multiple periods.

Custom Indicators: Flexibility to program and integrate personal strategies.

Automation and Algorithmic Trading

Automation is indispensable for modern forex trading. Platforms like cTrader and NinjaTrader excel with features like:

Pre-built Strategies: Ready-to-use templates for scalping and trend following.

Custom Algorithms: Integration with programming languages such as C# and Python.

Backtesting: Evaluate strategies with historical data.

Integration with APIs: Seamless syncing with advanced trading bots.

Mobile Accessibility

Forex traders increasingly require the flexibility of trading on-the-go. Mobile accessibility ensures:

Synchronization: Real-time updates between desktop and mobile devices.

Push Notifications: Alerts for market changes and trade execution.

Compact Design: Optimized for smaller screens without losing functionality.

App Examples: MT4 and MT5 apps, offering full trading capabilities on iOS and Android.

Key Takeaway: Platforms combining a robust desktop experience with seamless mobile integration empower traders with unmatched convenience.

The best forex trading platforms for 2025 excel in usability, advanced charting, automation, and mobile functionality. By integrating these features, platforms like MT5, cTrader, and TradingView offer versatile solutions for traders of all expertise levels.

Trading Instruments Supported by Leading Platforms

The diversity of trading instruments available on forex platforms is crucial for building effective strategies and achieving long-term trading success. This section explores the breadth and advantages of various trading instruments.

1. Major Currency Pairs

Major currency pairs, such as EUR/USD, USD/JPY, and GBP/USD, dominate forex markets due to their high liquidity and tighter spreads. Leading platforms like MetaTrader 5 and TradingView offer advanced tools for analyzing these pairs, enabling traders to capitalize on predictable movements.

Key Features:

High liquidity ensures minimal price fluctuations during trades.

Access to real-time market data for precise decision-making.

Supported by most trading strategies, including scalping and swing trading.

These pairs are ideal for traders seeking consistent opportunities in stable market conditions.

2. Exotic Pairs

Exotic pairs combine major currencies with currencies from emerging markets, such as USD/TRY or EUR/SEK. While they offer higher potential rewards, they also come with increased volatility and wider spreads.

Risks and Rewards:

Volatility: Significant price movements create potential for larger profits.

Higher Spreads: Costs can be prohibitive for short-term trading strategies.

Economic Dependence: Price movements often correlate with specific geopolitical or economic conditions.

Platforms like cTrader often feature analytical tools tailored for exotic pair trading, helping traders manage the associated risks.

3. CFDs and Futures

Contracts for Difference (CFDs) and futures are derivatives enabling traders to speculate on forex price movements without owning the underlying assets. Futures contracts are often traded on platforms like NinjaTrader, while CFDs are supported on MetaTrader platforms.

CFDs vs. Futures in Forex Trading

Wider spreads but no commissionCommissions and exchange fees

CFDs and futures cater to traders seeking flexibility and hedging opportunities in volatile markets.

4. Spot Forex vs. Forward Contracts

Spot forex trades settle instantly at prevailing market rates, making them ideal for day traders. Forward contracts, however, lock in future exchange rates and are often used by businesses to hedge against currency fluctuations.

Spot Forex:

Instant execution for quick trades.

Supported by platforms like TradingView, which offers robust charting tools.

Forward Contracts:

Customizable settlement dates.

Reduced risk of unfavorable exchange rate changes.

Forward contracts are frequently utilized for long-term strategies requiring stability.

5. Options Trading in Forex

Forex options provide traders the right, but not the obligation, to buy or sell currencies at a predetermined price. Options trading is supported on platforms like MetaTrader 5, offering flexibility for speculative and hedging strategies.

Advantages:

Defined risk due to limited loss potential.

Compatibility with advanced trading strategies like straddles and strangles.

Access to multiple expiration dates for tailored strategies.

Options trading is an excellent choice for traders seeking diversification and controlled risk in uncertain markets.

Market Indicators for Effective Forex Trading Forex trading in 2025 requires mastery of market indicators for successful trades. Platforms integrating technical tools like RSI, Bollinger Bands, and Fibonacci retracements provide invaluable support for analyzing currency pairs and spotting trends.

1: Moving Averages and RSI

Moving averages and RSI (Relative Strength Index) are staples in forex trading for spotting trends and identifying overbought or oversold market conditions. Here's how they work:

Moving Averages:

Smooth out price data for better trend analysis.

Common types: Simple Moving Average (SMA) and Exponential Moving Average (EMA).

Platforms like MetaTrader 5 (MT5) allow customizable moving average periods for traders’ needs.

RSI:

Measures the speed and change of price movements.

Values above 70 indicate overbought conditions, while below 30 signals oversold.

Both indicators are excellent for detecting market reversals and consolidations, making them essential for scalping and swing trading strategies.

2: Bollinger Bands and Fibonacci Retracements

Bollinger Bands and Fibonacci retracements are complementary tools for determining price ranges and potential reversals.

Bollinger Bands:

Comprised of a central moving average and two bands (standard deviations).

Highlights volatility and identifies breakout opportunities in exotic pairs and minor pairs.

Fibonacci Retracements:

Based on key levels derived from the Fibonacci sequence (23.6%, 38.2%, 61.8%, etc.).

Used to forecast retracement zones for entry and exit points.

Platforms like TradingView provide advanced integration of these tools for technical analysis.

3: Pivot Points and Volume Analysis

Pivot points and volume analysis serve as complementary methods for intraday traders.

Pivot Points:

Calculate potential support and resistance levels based on previous trading sessions.

Widely used in day trading to set intraday targets.

Volume Analysis:

Measures market activity to validate price movements.

Higher volume during breakouts confirms trends.

Together, these indicators help traders plan risk-reward ratios effectively and refine strategies. Platforms offering integrated market indicators like RSI, Fibonacci retracements, and volume analysis provide forex traders with precise insights for decision-making. Combining these tools with strategic risk management and discipline ensures a competitive edge in forex trading for 2025.

Risk Management Tools in Forex Platforms

Risk management is the cornerstone of sustainable forex trading. Platforms offering advanced tools like Stop-Loss Orders and Position Sizing empower traders to mitigate risks while optimizing potential gains.

1. Stop-Loss Orders

Stop-loss orders safeguard capital by automatically closing trades at pre-set levels. Key benefits include:

Capital Protection: Prevents losses from spiraling during volatile markets.

Emotional Discipline: Reduces impulsive decisions by automating exit points.

Wide Platform Integration: Available on MetaTrader 4, TradingView, and cTrader for seamless trading execution.

2. Take-Profit Orders

Take-profit orders lock in profits when the market reaches a target price. Steps for setting take-profit orders effectively:

Analyze Moving Averages and RSI to determine target levels.

Input the price level in trading platforms like NinjaTrader or MT5.

Monitor trade performance and adjust as needed.

3. Position Sizing Calculators

Accurate position sizing minimizes overexposure to any single trade. Here’s how these calculators work:

Calculate lot sizes based on account balance, risk percentage, and stop-loss distance.

Adjust trade sizes to align with Risk-Reward Ratios.

Enable traders to maintain diversified exposure.

4. Risk-Reward Ratio Analysis

Risk-reward ratios evaluate trade viability by comparing potential profits to losses. Tips for effective use:

Aim for a minimum ratio of 1:2 or higher.

Utilize tools like Bollinger Bands to estimate price movements.

Integrated calculators on platforms like MT4 simplify these computations.

5. Diversification Tools

Diversification spreads risk across multiple trading instruments. Features on platforms include:

Multi-asset trading options: CFDs, Futures, and Currency Pairs.

Portfolio analysis tools to track exposure by instrument type.

Real-time updates for Exotic Pairs and niche markets.

6. Backtesting Strategies

Backtesting allows traders to evaluate strategies using historical data. Its advantages are:

Testing risk management techniques like Stop-Loss Orders without live market risk.

Platforms such as TradingView support customizable backtesting scripts.

Insights into strategy weaknesses improve long-term profitability.

With advanced tools for Stop-Loss Orders, Position Sizing, and Backtesting, modern forex trading platforms empower traders to proactively manage risks. Leveraging these features leads to more disciplined and effective trading.

Psychological and Strategic Insights for Forex Trading

Mastering trading psychology is key to navigating the complexities of forex. Platforms enhance this through features that promote discipline, performance tracking, and trader confidence, empowering strategic growth and mitigating psychological pitfalls.

Building Discipline Through Alerts

Platforms offering robust alert systems, like MetaTrader 5, help instill discipline by:

Preventing Overtrading: Custom alerts signal market entry points, limiting impulsive trades.

Time Management: Reminders help traders stick to predefined schedules.

Market Trend Notifications: Alerts for moving averages or Relative Strength Index (RSI) changes enable focused decisions.

Tracking Performance Metrics

Trading platforms integrate tools that help traders evaluate performance, including:

Win/Loss Ratio Analysis: Shows trade success rates.

Equity Curve Monitoring: Visualizes account performance trends.

Journal Features: Logs trade entries and exits for review.

Customizable Dashboards

Platforms like TradingView allow traders to configure dashboards by:

Adding favorite currency pairs and indicators like MACD or Bollinger Bands.

Creating multi-screen setups to monitor multiple trades.

Integrating news feeds to stay updated with central bank announcements.

Educational Resources

The inclusion of in-platform education fosters confidence through:

Interactive Tutorials: Step-by-step videos on strategies like swing trading or technical analysis.

Webinars and Live Sessions: Experts discuss trading instruments like CFDs and options.

AI-based Learning Modules: Adaptive lessons based on trader performance.

By integrating tools for discipline, self-awareness, and strategy refinement, trading platforms empower users to overcome psychological challenges, enhance risk management, and make data-driven decisions for long-term success.

Conclusion

Forex trading in 2025 offers exciting opportunities, but success begins with choosing the right platform. As highlighted throughout this content pillar, top trading platforms like MetaTrader 4 (MT4), MetaTrader 5 (MT5), cTrader, and TradingView stand out for their robust features, diverse trading instruments, and advanced integrations. These platforms empower traders to navigate the complexities of the forex market through tools such as technical indicators like Moving Averages and RSI, risk management solutions like stop-loss orders and position sizing calculators, and integrations with vital economic indicators such as GDP, inflation, and central bank announcements.

The best forex trading platforms not only provide access to currency pairs, CFDs, and other instruments but also integrate cutting-edge charting tools, educational resources, and analytics to build confidence and discipline—critical factors in mastering the psychological demands of trading.

By understanding the interplay between platform features, market tools, and strategy development, traders can optimize their approach to trading forex in 2025. Whether you're focused on scalping, day trading, or long-term swing trading, the right platform will be your foundation for executing trades effectively, managing risk, and staying informed in a fast-paced market.

Take the insights from this guide to make an informed decision, choosing a platform that aligns with your trading goals and enhances your ability to trade forex with precision and confidence. With the right tools and strategies in hand, you're poised to navigate the evolving forex market and unlock its full potential in 2025 and beyond.

[bloobluebloo]

Hello!

This might be a weird question, but since you work in IT, do you use AI tools like ChatGPT or Claude a lot, or not at all? I’ve been learning programming for a few months, and honestly, it’s super hard. I’m definitely not a genius, so I use AI a lot to help me figure out what I’m doing and generate code.

The problem is that other students kind of judge and look down on people who use these tools, and it’s making me feel bad about it. Should I stop using AI altogether? I just don’t know how to manage without help or researching all the time.

If you have any tips, they'd really help me out 🙏

Thanks for reading this!

Hey anon! Well, the thing is that the IT industry in its entirety is pushing for AI integration as a whole into their products, so industry-wise it has become sort of inevitable. That being said, because we are still early into the adoption of AI I personally don't use it as I don't have much of a need for it in my current projects. However, Github Copilot is a tool that a lot of my colleagues like to use to assist with their code, and IDEs like IntelliJ have also begun to integrate AI coding assistance into their software. Some of my colleagues do use ChatGPT to ask very obscure and intricate questions about some topics, less to do with getting a direct answer and moreso to get a general idea of what they should be looking at which will segway into my next point. So code generation. The thing is, before the advent of ChatGPT, there already existed plenty of tools that generate boilerplate templates for code. As a software engineer, you don't want to be wasting time reinventing the wheel, so we are already accustomed to using tools to generate code. Where your work actually comes in is writing the logic that is very specific to the way that your project functions. The way I see ChatGPT is that it's a bit smarter than the general libraries and APIs we already use to generate code, but it still doesn't take the entire scope of your project into consideration. The point I am getting at here is that I don't necessarily think there is a problem in generating code, whether you are using AI or anything else, but the problem is do you understand what the code is doing, why it works, and how it will affect your project? Can you take what ChatGPT gives you and actually optimize it to the specifics of your project, or do you just inject it, see that it works, and go on your merry way without another thought as to why it worked? So, I would say, as a student, I would suggest trying not to use ChatGPT to generate code, because it defeats the purpose of learning code. Software engineering as a whole is tough! It is actually the nature of the beast that, at times, you will spend hours trying to solve a specific problem, and often times the solution at the end is to add one line in one very specific place which can feel anticlimactic after so much effort. However, what you get from all those hours of debugging, researching, and asking questions is a wealth of knowledge that you can add to your toolbox, and that is what is most important as a software developer. The IT landscape is rapidly changing; you might be expected to pick up a different programming language and different framework within weeks, you might suddenly be saddled with a new project you've never seen in your life, or you might suddenly have something new like AI thrown at you where you suddenly have to take it into consideration in your current work. You can only keep up with this sort of environment if you have a good understanding of programming fundamentals. So, try not to lean too much on things like ChatGPT because it will get you through today, but it will hurt you down the line (like in tech interviews, for example).

[obanicrypto]

Unlocking New Possibilities with the STON.fi API & SDK Demo App

Have you ever faced a moment in your development journey where you wanted to integrate a powerful feature but didn’t know where to start? That’s a common feeling, especially in the blockchain space where innovation moves faster than most of us can keep up with. I’ve been there, too, and that’s why I’m excited to share something that will make your work simpler and more impactful—the STON.fi API & SDK Demo App.

This isn’t just another tool in the blockchain world; it’s a resource designed to give you clarity and confidence when building on the TON ecosystem.

What Is the STON.fi Demo App All About

Let’s start with a quick analogy. Think of building a blockchain app like constructing a house. You need the right tools and a clear blueprint. The STON.fi demo app is like a pre-built room that shows you exactly how everything fits together. You can study it, replicate it, and adapt it to your project.

This app showcases how to seamlessly integrate STON.fi’s swap function using its API and SDK. It’s a working example that’s not just theoretical—it’s real, functional, and ready to inspire your next project.

Why Does This Matter

Let’s make this relatable. Imagine you’re tasked with creating a crypto wallet that allows users to swap tokens. Without guidance, you’d spend hours (or even days) trying to figure out the right implementation. The STON.fi demo app eliminates that guesswork.

Here’s why it’s a big deal:

1. It’s a Hands-On Guide

You don’t have to learn by trial and error. The demo gives you a live example of how everything works, so you’re not starting from scratch.

2. Saves Time and Energy

Time is money, especially in tech. Instead of spending countless hours debugging, you can focus on customizing and enhancing your app.

3. Showcases the Full Potential of STON.fi

The demo isn’t limited to swaps—it’s a showcase of how versatile and powerful the STON.fi SDK can be.

Real-Life Applications

Here’s where it gets exciting. Whether you’re a solo developer or part of a team, this demo app can simplify your work and spark new ideas.

Let’s say you’re building a decentralized exchange (DEX). Token swaps are a core feature, but implementing them can feel overwhelming. The STON.fi demo app gives you a starting point that’s already proven to work.

Or maybe you’re creating a DeFi lending platform. Adding a token swap feature can enhance your offering, making it more attractive to users. The demo app provides the tools you need to make that happen without reinventing the wheel.

Breaking Down the Benefits

Think of this as a tool that bridges the gap between “I want to build this” and “I just built this.”

1. Clarity in Implementation: The app gives you a clear example of how to integrate STON.fi’s features. It’s like having a mentor guide you through the process.

2. Reduced Complexity: Blockchain development can feel like trying to solve a Rubik’s cube blindfolded. This app removes unnecessary complexity, allowing you to focus on what matters.

3. Endless Inspiration: Beyond swaps, this demo can inspire you to explore other possibilities within the TON ecosystem.

Why I Believe This Matters

I remember when I first started exploring blockchain development. Every step felt like climbing a mountain, and sometimes I wasn’t even sure if I was on the right trail. Resources like the STON.fi demo app would have made a world of difference back then.

This tool isn’t just for seasoned developers—it’s for anyone looking to make their mark in the blockchain space. It’s accessible, practical, and built to help you succeed.

Try the SDK

Final Thoughts

The STON.fi API & SDK Demo App isn’t just a resource; it’s a catalyst for creativity and innovation. Whether you’re building your first app or looking to level up an existing project, this demo provides the clarity and direction you need.

Take the time to explore it, experiment with it, and let it inspire your next big idea. In a space as dynamic as blockchain, having the right tools can make all the difference.

This is your opportunity to simplify your process, save time, and unlock the full potential of the TON ecosystem. Don’t just take my word for it—try it out and see what’s possible.