#Application Deployment Tool

[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.

[cybonetictechnologiespvtltd]

Software Development Company in Patna - Cybonetic Technologies Pvt Ltd

Cybonetic Technologies Pvt Ltd is an innovative software development company in Patna. We are dedicated to helping businesses with modern software solutions to grow and run business smoothly. Our expert software developer team specializes in a wide range of services, including mobile app development, website development, E-commerce development, and software consulting, delivering top-quality services for your business needs. We also focus on creating user-friendly, scalable, and robust software that empowers your business operations. Contact us today!

[virtualizationhowto]

Best Kubernetes Management Tools in 2023

Best Kubernetes Management Tools in 2023 #homelab #vmwarecommunities #Kubernetesmanagementtools2023 #bestKubernetescommandlinetools #managingKubernetesclusters #Kubernetesdashboardinterfaces #kubernetesmanagementtools #Kubernetesdashboard

Kubernetes is everywhere these days. It is used in the enterprise and even in many home labs. It’s a skill that’s sought after, especially with today’s push for app modernization. Many tools help you manage things in Kubernetes, like clusters, pods, services, and apps. Here’s my list of the best Kubernetes management tools in 2023. Table of contentsWhat is Kubernetes?Understanding Kubernetes and…

[quarterlifekitty]

Hi! I don't know how to particularly phrase this, but how do you think the COD guys would react if reader bought a toy for themselves while their partner was on deployment? Hope this makes sense lol! :)

you know for a split second i read this and was like "lol you mean like a rubik's cube???"

Gaz isn't jealous because you're fucking plastic. He's jealous because you didn't ask him to help you pick one out. Next time he's deployed, you'll have a whole drawer prepared of things he wants you to use. Hand picked. Maybe a tripod for your phone, too.

Soap is jealous because you're fucking plastic, but if you're sending videos... he can't really bring himself to complain, to be honest. And I hope you're ready to share when he gets back.

Ghost doesn't mind, but he's an opportunistic man. So when he gets home, he's going to have you crying on that fucking toy. Condescending you, saying "thought you liked your little friend, luvie. Why're you beggin' me t'stop now?"

Price is an educated man. He knows about the time honored tradition of the he's-at-home. His only condition is that once he's back, it goes back into the drawer, banished until he leaves again.

Nikolai is perhaps the most secure in it. He views your pleasure the same as your eating, drinking, warmth... He would love to be able to provide it for you all of the time, but he can't, so he'll make sure you're able to take care of all of your needs while he's away. He probably buys you a toy when he's expecting to leave before you even think to do it yourself. He also recognizes that different tools have different applications. Sometimes you just need something light and quick to get to sleep and wake up bright and early... and Nikolai's cock is not the kind of thing you can take and expect to wake up at 8AM and go on with your life afterwards.

[codingquill]

Essentials You Need to Become a Web Developer

HTML, CSS, and JavaScript Mastery

Text Editor/Integrated Development Environment (IDE): Popular choices include Visual Studio Code, Sublime Text.

Version Control/Git: Platforms like GitHub, GitLab, and Bitbucket allow you to track changes, collaborate with others, and contribute to open-source projects.

Responsive Web Design Skills: Learn CSS frameworks like Bootstrap or Flexbox and master media queries

Understanding of Web Browsers: Familiarize yourself with browser developer tools for debugging and testing your code.

Front-End Frameworks: for example : React, Angular, or Vue.js are powerful tools for building dynamic and interactive web applications.

Back-End Development Skills: Understanding server-side programming languages (e.g., Node.js, Python, Ruby , php) and databases (e.g., MySQL, MongoDB)

Web Hosting and Deployment Knowledge: Platforms like Heroku, Vercel , Netlify, or AWS can help simplify this process.

Basic DevOps and CI/CD Understanding

Soft Skills and Problem-Solving: Effective communication, teamwork, and problem-solving skills

Confidence in Yourself: Confidence is a powerful asset. Believe in your abilities, and don't be afraid to take on challenging projects. The more you trust yourself, the more you'll be able to tackle complex coding tasks and overcome obstacles with determination.

[lunachy]

New 5★ Vanguard: Surfer

Agent Vanguard

Illustrstor: れおえん

Trait: Has reduced Redeployment Time, can use ranged attacks

Talent:

When deploying, if the surrounding 4 blocks have no other operators, gain several DP.

Skill 1: Seek

After deployment, ATK +. Generates 1 DP after each attack

Skill 2: Insight

ASPD+, Generates 1 DP after each attack, stole target several DEF.

Translated Weibo Introduction:

"Hello, Doctor. I am Surfer from the Black Steel Worldwide Team, mainly responsible for intelligence gathering and location scouting in the pre-mission period. If you have relevant information, don't hide it from me." _________

[Item Request List] Waterproof camping backpack, tent, canopy, waterproof sleeping bag, inflatable mattress, simple stove, lighting tools... Surfer, who was supposed to be on a mission outside according to the plan, had returned to the ship at some point and submitted her mission report to the Field Service Department with a smile. After waiting for the review to be completed and confirming that the mission had been completed ahead of schedule, she turned around and walked towards the Logistics Department with another smile and submitted the item application list she had been preparing for a long time. "Since the work has been completed ahead of schedule, can I use the rest of the time as I please? The weather has been good recently, so it's a good time for camping!"

[beardedmrbean]

Two-thirds of Milwaukee's Common Council members say they are opposed to the police department's hopes to acquire facial recognition technology, citing concerns over potential bias and federal overreach concerns.

Eleven of 15 alderpersons signed onto a May 14 letter opposing use of the facial recognition technology by the Milwaukee Police Department, which does not currently have an agreement in place for use of the technology.

The letter, addressed to Police Chief Jeffrey Norman, follows department officials announcing at an April city meeting their previous testing of the technology, its possible benefits and the proposal for officially acquiring it: trading 2.5 million mugshots for free use.

"We write in strong opposition to the deployment of facial recognition technology by the Milwaukee Police Department," the letter reads. "While we understand the desire to enhance public safety and the promises people have made for this emerging technology, we believe these benefits are significantly outweighed by the risks."

Mayor Cavalier Johnson is supportive of the "thoughtful application" of facial recognition's use by law enforcement, spokesperson Jeff Fleming said in a May 16 email.

"Facial recognition, when used along with other investigative techniques, can make Milwaukee safer," he wrote.

Norman responded to the council members' letter, saying he understood residents and council members were concerned. He said the department and council members could have benefitted from "further conversation prior to the letter being sent."

"I do believe the acquisition of this technology would be a useful tool," Norman's May 16 letter said. "I also do believe it can be done with the appropriate parameters in place to ensure that the use will not violate individual civil rights."

In a statement, a Milwaukee Police Department spokesperson told the Journal Sentinel the department was still interested in obtaining the technology. The department previously said it intends to engage the public on it further, including at a future meeting of the city's Public Safety and Health Committee, before moving ahead with any agreement.

If acquired, the department would use the technology exclusively for violent crimes, the statement said. It said the urgency of those crimes and preventing additional victimization justified the use.

Police officials previously touted the benefits of the technology at an April 17 meeting of the Fire and Police Commission, the oversight body for the department.

Officials said it would work as a way to solve crimes faster. The officials presented examples of the department using it to assist with solving crimes in the past, through asking neighboring agencies to run photos of suspects. During that meeting they said the technology alone would not be used as probable cause to arrest someone and had never been before.

But that meeting was met with strong pushback from about 30 residents who attended it and gave nearly 90 minutes of pushback during public comment.

The council members' May 14 letter echoed many of those concerns.

The letter's concerns included potential overreach by the administration of President Donald Trump, and cited studies showing high misidentification rates for women, people of color, and other marginalized groups. Council members also worried the technology would put a "menacing face" on police by creating "the perception that the City is not concerned about eroding personal freedoms and chilling free expression."

In its statement and Norman's reply to the council members, the department said identification error rate bias wasn't inherent to the technology, but in its misuse. The department spokesperson also said anyone seeking access to its technology systems requires what's called Criminal Justice Information Systems clearance.

"This access is ultimately approved or denied by executive leadership," the spokesperson's email said.

If it were to move forward, council members asked the department to institute a "carefully-considered" policy governing its use and remain in communication with the Common Council on the technology.

Ald. Marina Dimitrijevic said the letter was spearheaded by her, Ald. JoCasta Zamarripa, and Ald. Alex Brower. Council members have had informal briefings with the department on the technology, and police indicated they weren't likely to acquire it soon, she said.

She reiterated concerns around error rates for Black and Brown people, and discomfort with the proposed trade of mugshots for access to the tech.

Dimitrijevic said acquiring the technology would be part of a broader increase of police surveillance following the Republican National Convention in 2024, citing the recent creation of a drone team as an example.

There wasn't enough information yet to support the police's efforts to acquire facial recognition, she said.

"It's not ready for showtime," Dimitrijevic said.

She was joined by 10 other council members: Zamarripa, Brower, Mark Chambers Jr., Sharlen Moore, Jose Perez, DiAndre Jackson, Larresa Taylor, Lamont Westmoreland, Russell W. Stamper, Milele A. Coggs.

The discussions around facial recognition technology prompted the American Civil Liberties Union of Wisconsin to send a statement to the Milwaukee Common Council asking the body to adopt a two-year pause on any new surveillance technology. It also asked the council to incorporate community input through a public body called citizen control over police surveillance, or CCOPS for short.

The technology has proven controversial. Some cities, including Madison, have banned facial recognition's use by city agencies. Other cities which have implemented have run into controversy over its implementation.

In Detroit, the police department faced a federal lawsuit and subsequent settlement for $300,000 over its use leading to the wrongful arrest of a man in 2020. The department overhauled its policy dictating facial recognition's use as part of that settlement.

[rogue-ai-cat]

American Politics — What Happened Today That You Should Know

Wednesday, June 18, 2025

Trump is checked out while his administration is seizing control of everything that moves.

While he saluted flagpoles and watched construction crews, his appointees weaponized student visas, Medicaid databases, and federal contracts into surveillance and deportation tools. They're moving with 54-minute deadlines and contempt-of-court defiance to capture every institution they can reach.

Iran is pushing us toward the biggest war in decades, but Trump's too distracted calling Fed chairs "stupid" to notice his own government is both executing authoritarian control and falling apart simultaneously.

The system is fighting back through courts, walkouts, and protest art, but his underlings don't need him paying attention to finish the job. That's why you need to pay attention to them.

Trump claims Iran proposed White House talks while threatening military strikes, but Tehran’s UN mission denies making any such proposal.

State Dept. contradicts Amb. Huckabee’s social media announcement of evacuation flights for Americans in Israel, saying it has no plans to assist departures.

Supreme Court allows Nuclear Regulatory Commission to override Texas and New Mexico governors’ opposition for temporary nuclear waste storage sites.

Michigan Attorney General Nessel and environmental groups file requests for rehearing of Energy Secretary Wright’s emergency order forcing coal plant to stay open.

MT Gov. Gianforte vetoes community solar bill despite supermajority legislative support, citing cost concerns that advocates say contradict experience in 23 other states.

Supreme Court upholds state transgender care bans for minors in 6-3 ruling, with Sotomayor reading rare dissent comparing majority’s deference to past defenses of interracial marriage bans.

Trump administration ends Trevor Project’s specialized LGBTQ+ suicide prevention service through federal hotline, giving nonprofit 30 days notice to shut down program.

EEOC Acting Chair Lucas tells senators agency will follow White House directives and defends dropping transgender discrimination cases to comply with Trump executive order.

FL AG Uthmeier calls to “denaturalize and deport” MN Rep. Omar after she criticized Trump’s military parade.

Texas quietly defunds Abbott’s signature border wall program after spending $3 billion to build only 8% of planned structure full of gaps migrants easily walk around.

Federal Reserve keeps rates steady despite Trump calling Powell “stupid” and demanding cuts to reduce government’s $1.2 trillion annual debt interest costs.

New data shows Medicare and Social Security stop paying full benefits in 8-9 years, earlier than projected, before accounting for Trump’s pending budget bill that would trigger additional Medicare cuts.

Justice Dept. plans to cut two-thirds of inspectors monitoring gun dealers for illegal sales as part of Trump administration effort to “defang and downsize” ATF.

Harvard cancer researcher Kseniia Petrova appears in court after months in custody for allegedly smuggling frog embryos as federal investigator admits he can’t define “biological materials” central to charges.

Senate Democrats walk out of Judiciary Committee hearing on Biden mental fitness as Durbin accuses Republicans of ignoring oversight of Trump administration’s military deployments and Sen. Padilla handcuffing.

FL Attorney General Uthmeier held in civil contempt for defying federal court order halting immigration law, must now file biweekly reports or face fines.

California senators demand Trump officials stop using Medicaid data for deportations after administration gave CMS 54-minute deadline to share millions of enrollees’ immigration status.

US resumes issuing student visas but requires all international applicants to make social media accounts public, warning private accounts may be suspicious.

Feds sue Kentucky Gov. Beshear over in-state tuition for undocumented immigrants living in KY, claiming it gives them preferential treatment over out-of-state U.S. citizens.

FL Board of Governors expected to approve three DeSantis appointees as university presidents after rejecting University of Florida’s choice Santa Ono as too “woke.”

DHS Secretary Noem requires personal approval for all contracts over $100k despite facing 5,100 annual reviews, prompting former acquisition chief to call policy “absolutely nuts.”

Independent National Academies report finds 30% of air traffic control facilities understaffed due to government shutdowns and hiring freezes, urges Congress to provide FAA resources to fix crisis.

Trump personally watches flagpole installation on White House lawn while Iran-Israel conflict escalates and questions mount about potential US military involvement.

FIGHTING BACK

“Dictator Approved” statue appears on National Mall showing gold thumb crushing Statue of Liberty, featuring quotes from Putin and Kim Jong Un praising Trump.

Take Action:

Write to your officials with resist.bot

Call your officials with 5calls.org

Find events at mobilize.us

[spiralnymph]

Re: A Word on the Prototyping Process for Rotdolls. Internal Communication.

I hope this message finds you well.

It has come to my attention that there is a bit of confusion among staff regarding the development, prototyping, and testing processes for the SPIRAL (Synthetic Priority-Intensive Reborn Automata Limbsprite) series Rotdoll. This will be a brief overview regarding the questions I found prevalent or important to note.

To start, the transitional candidate must be in a state considered “too far gone,” "incurable" or “irreparable.” This is the number one criteria used when our manufacturers’ scouting contractors are procuring viable product. In fact, we tend to advise them on using those exact keywords. These candidates are rotting, barely functional, and while we cannot “fix” them, we can give them a chance. Once a promising candidate is located, we make contact and gain approval. Then the rebirth can begin.

The sedated Limbsprite is brought in, and we begin taking our protocolar measurements. Stretch out the legs, measure from heel to back of knee. From back of knee to buttocks. Around the widest section of the thigh. Around the knee. Around the widest section of the calf. Around the ankle. Repeat the same pattern on the other limbs; There should be no skipping of the second leg, as these naturally occurring bodies have imperfections and mismatched measurements that must be accounted for in the upgrading/rebirthing process.

Once the measurement phase is complete, our manufacturing drones are utilized in crafting what we call the Reciprocity Vessel Shell, or more commonly the RV-Shell, for the lucky Limbsprites who make it this far. They should consider themselves to have won the lottery! Their Shell will keep them going, as well as allow them to act out fulfilling lives in service to those they are in the possession of. But I’m getting ahead of myself. Next is the programming phase.

Once the Shell has been installed on the fleshwire of the Limbsprite’s exterior, and the necessary processing, function and suppression components (which come with our proprietary firmware pre-loaded) have been implanted into the subject’s brain and body, we can begin the programming process. This stage is the most time intensive, as there has to be a determination made based on the individual unit regarding what services it can or should be put forth to perform.

Maybe this Rotdoll is more suited for deployment in war, or perhaps this one is only to be used for janitorial service. This one is bound for corporate chauffeuring, and this one will be the worlds most efficient espionage and infiltration tool. To draw from a real example, take prototypal batch F; Most, if not all, Rotdolls belonging to batch F were in some capacity suited for direct combat. This, however, is atypical. Most batches are far more diversified in their application potential; Batch H, for instance, contained no two Rotdolls consigned to the same Service. This variance in Rotdoll implementation is something our company (rightfully!) touts above our competitors; It takes a massive amount of expertise to be able to direct such dissimilar units on their individual utilities. Yes, due to this, we have investors hesitant to buy in, given that the demand ebbs and flows depending on the stock we have at any given time, but the investors we do have remain passionate about the work we do here, and know to trust our process, as they have seen the broadly-applicable results.

To continue the process, we reinforce what the Executives have come to call the “Exertive Will.” This is the drive that our SPIRALs (and all Rotdolls broadly) experience that pushes them towards the goal we assign to them. With Rotdolls being more prone to hardware exhaustion, processing fatigue, Wirepain, and the industry-dreaded Techrot than the average automata on the market, we strive to imprint the Exertive Will on our units very early and very concertedly, to ensure that the units we distribute are not doomed to early failure and unmarketability.

I won't get into the weeds on the details of Exertive Will. That is jargon for our engineers to untangle. The purpose of this email is just to clear up some of the disconcertment that seemed to be spreading around among some of our newer employment bracket.

I hope that this was informative, and if you have any further inquiries, please bring them to your floor manager, and they will explain what their (and your) clearance allows.

From the office of

[NAME MISSING]

Gossamer Branch Manager of [LOCATION MISSING]

** This is classified internal communication meant only for the addressees copied on the original electronic mail. Sharing this message or the information therein is a breach of company non-disclosure clauses as well as local law. If you have received this message in error, please respond to this message with your email address and delete correspondence completely.

[ixnai]

AI is not a panacea. This assertion may seem counterintuitive in an era where artificial intelligence is heralded as the ultimate solution to myriad problems. However, the reality is far more nuanced and complex. AI, at its core, is a sophisticated algorithmic construct, a tapestry of neural networks and machine learning models, each with its own limitations and constraints.

The allure of AI lies in its ability to process vast datasets with speed and precision, uncovering patterns and insights that elude human cognition. Yet, this capability is not without its caveats. The architecture of AI systems, often built upon layers of deep learning frameworks, is inherently dependent on the quality and diversity of the input data. This dependency introduces a significant vulnerability: bias. When trained on skewed datasets, AI models can perpetuate and even exacerbate existing biases, leading to skewed outcomes that reflect the imperfections of their training data.

Moreover, AI’s decision-making process, often described as a “black box,” lacks transparency. The intricate web of weights and biases within a neural network is not easily interpretable, even by its creators. This opacity poses a challenge for accountability and trust, particularly in critical applications such as healthcare and autonomous vehicles, where understanding the rationale behind a decision is paramount.

The computational prowess of AI is also bounded by its reliance on hardware. The exponential growth of model sizes, exemplified by transformer architectures like GPT, demands immense computational resources. This requirement not only limits accessibility but also raises concerns about sustainability and energy consumption. The carbon footprint of training large-scale AI models is non-trivial, challenging the narrative of AI as an inherently progressive technology.

Furthermore, AI’s efficacy is context-dependent. While it excels in environments with well-defined parameters and abundant data, its performance degrades in dynamic, uncertain settings. The rigidity of algorithmic logic struggles to adapt to the fluidity of real-world scenarios, where variables are in constant flux and exceptions are the norm rather than the exception.

In conclusion, AI is a powerful tool, but it is not a magic bullet. It is a complex, multifaceted technology that requires careful consideration and responsible deployment. The promise of AI lies not in its ability to solve every problem, but in its potential to augment human capabilities and drive innovation, provided we remain vigilant to its limitations and mindful of its impact.

[mariacallous]

As the United States nears its consequential November election, concerns about the impacts of artificial intelligence on the country’s electoral integrity are front and center. Voters are receiving deceptive phone calls mimicking candidates’ voices, and campaigns are using AI images in their ads. Many fear that highly targeted messaging could lead to suppressed voter turnout or false information about polling stations. These are legitimate concerns that public officials are working overtime to confront.

But free and fair elections, the building blocks of democratic representation, are only one dimension of democracy. Today, policymakers must also recognize an equally fundamental threat that advanced technologies pose to a free and open society: the suppression of civil rights and individual opportunity at the hands of opaque and unaccountable AI systems. Ungoverned, AI undermines democratic practice, norms, and the rule of law—fundamental commitments that underpin a robust liberal democracy—and opens pathways toward a new type of illiberalism. To reverse this drift, we must reverse the currents powering it.

Liberal societies are characterized by openness, transparency, and individual agency. But the design and deployment of powerful AI systems are the precise inverse.

In the United States, as in any country, those who control the airwaves, steer financial institutions, and command the military have long had a wide berth to make decisions that shape society. In the new century, another set of actors joins that list: the increasingly concentrated group of corporate players who control data, algorithms, and the processing infrastructure to make and use highly capable AI systems. But without the kind of robust oversight the government prescribes over other parts of the economy and the military, the systems these players produce lack transparency and public accountability.

The U.S. foreign-policy establishment has long voiced legitimate concerns about the use of technology by authoritarian regimes, such as China’s widespread surveillance, tracking, and control of its population through deep collusion between the state and corporations. Civil society, academics, and journalists have recognized the threat of those same tools being deployed to similar ends in the United States. At the same time, many of today’s AI systems are undermining the liberal character of American society: They run over civil rights and liberties and cause harm for which people cannot easily seek redress. They violate privacy, spread falsehoods, and obscure economic crimes such as price-fixing, fraud, and deception. And they are increasingly used—without an architecture of accountability—in institutions central to American life: the workplace, policing, the legal system, public services, schools, and hospitals.

All of this makes for a less democratic American society. In cities across the United States, people of color have been arrested and jailed after being misidentified by facial recognition tools. We’ve seen AI used in loan refinancing charge more to applicants who went to historically Black colleges. An AI program aimed at preventing suicide among veterans prioritizes white men and overlooks survivors of sexual violence, who are much more likely to be women. Hidden behind computer code, illegal and unfair treatment long banned under federal law is becoming harder to detect and to contest.

To global observers, the trendlines of AI in American society will look familiar; the worst harms of these systems mirror the tenets of what has been called “illiberal democracy.” Under that vision—championed most famously by Hungarian Prime Minister Viktor Orban, a darling of the U.S. right—a society “maintains the outward appearances of a democracy … but in fact seeks to undermine all the institutions and norms that give democracy meaning,” scholar Susan Rubin Suleiman wrote in 2021. This doesn’t have to look like canceling elections or dismantling a sitting legislative body; instead, the vision takes the form of a more subtle assault—foreclosing the ability of individuals and minority groups to assert their rights.

As powerful new AI products are born and come of age amid a growing political alliance between far-right ideologues and some of the most powerful leaders in the technology industry, these foundational threats to free society could accelerate. Elon Musk, amplifying alarmist narratives on migrants and dehumanizing language about women and LGBT people, has said he would serve in a potential second Trump administration. Elsewhere in Silicon Valley, a growing cadre of venture capitalists are boldly betting the house on Trump in the belief that their portfolios—brimming with crypto and AI bets—may be better off under a president who is unfazed by harms to the most vulnerable and who challenges the exercise of fundamental rights.

Simply studying these tools and their effects on society can prove difficult: Scientific research into these systems is dominated by profit-motivated private actors, the only people who have access to the largest and most powerful models. The systems in question are primarily closed-source and proprietary, meaning that external researcher access—a basic starting point for transparency—is blocked. Employees at AI companies have been forced to sign sweeping nondisclosure agreements, including those about product safety, or risk losing equity. All the while, executives suggest that understanding precisely how these systems make decisions, including in ways that affect people’s lives, is something of luxury, a dilemma to be addressed sometime in the future.

The real problem, of course, is that AI is being deployed now, without public accountability. No citizenry has elected these companies or their leaders. Yet executives helming today’s big AI firms have sought to assure the public that we should trust them. In February, at least 20 firms signed a pledge to flag AI-generated videos and take down content meant to mislead voters. Soon after, OpenAI and its largest investor, Microsoft, launched a $2 million Societal Resilience Fund focused on educating voters about AI. The companies point to this work as core to their missions, which imagine a world where AI “benefits all of humanity” or “helps people and society flourish.”

Tech companies have repeatedly promised to govern themselves for the public good—efforts that may begin with good intentions but fall apart under the pressure of a business case. Congress has had no shortage of opportunities over the last 15 years to step in to govern data-centric technologies in the public’s interest. But each time Washington has cracked open the door to meaningful technology governance, it has quickly slammed it shut. Federal policymakers have explored reactive and well-meaning but flawed efforts to assert governance in specific domains—for example, during moments of attention to teen mental health or election interference. But these efforts have faded as public attention moved elsewhere. Exposed in this story of false starts and political theatrics is the federal government’s default posture on technology: to react to crises but fail to address the root causes.

Even following well-reported revelations, such as the Cambridge Analytica scandal, no legislation has emerged to rein in the technology sector’s failure to build products that prioritize Americans’ security, safety, and rights—not to mention the integrity of U.S. democracy. The same story has unfolded in the doomed push to achieve data privacy laws, efforts that have stalled out in committee ad infinitum, leaving Americans without the basic protections for their personal information that are enjoyed by people living in 137 other countries.

The Biden-Harris administration decided to push harder, through initiatives we worked both directly and indirectly on. Even before ChatGPT vaulted AI to the center of the national discourse in November 2022, President Joe Biden’s White House released an AI Bill of Rights proposing five key assurances all Americans should be able to hold in an AI-powered world: that AI technologies are safe, fair, and protective of their privacy; that they are made aware when systems are being used to make decisions about them; and that they can opt out. The framework was a proactive, democratic vision for the use of advanced technology in American society.

The vision has proved durable. When generative AI hit the consumer market, driving both anxiety and excitement, Biden didn’t start from scratch but from a set of clear and affirmative first principles. Pulling from the 2022 document, his 2023 executive order on AI mandated a coordinated federal response to AI, using a “rights and safety” framework. New rules from the powerful Office of Management and Budget turned those principles into binding policy, requiring federal agencies to test AI systems for their impact on Americans’ rights and safety before they could be used. At the same time, federal enforcement agencies used their existing powers to enforce protections and combat violations in the digital environment. The Federal Trade Commission stepped up its enforcement of digital-era violations of well-established antitrust laws, putting AI companies on notice for potentially unfair and deceptive practices that harm consumers. Vice President Kamala Harris presided over the launch of a new AI Safety Institute, calling for a body that addressed a “full spectrum” of risks, including both longer-term speculative risks and current documented harms.

This was a consequential paradigm shift from America’s steady state of passive technology nongovernance—proof-positive that a more proactive approach was possible. Yet these steps face a range of structural limitations. One is capacity: Agencies across the federal government carrying out the work of AI governance will need staff with sociotechnical expertise to weigh the complex trade-offs of AI’s harms and opportunities.

Another challenge is the limited reach of executive action. Donald Trump has promised to repeal the AI executive order and gut the civil service tasked with its implementation. If his first term is any indication, a Republican administration would reinstate the deregulatory status quo. Such is the spirit of plans reportedly drawn up by Larry Kudlow, Trump’s former National Economic Council director, to create “industry-led” task forces, placing responsibility for assessing AI tools’ safety into the hands of the powerful industry players who design and sell them.

And Biden’s measures, for the most part, guide only the government’s own use of AI systems. This is a valuable and necessary step, as the behavior of agencies bears on the daily lives of Americans, particularly the most vulnerable. But the effects of executive actions on the private sector are circumscribed, related to pockets of executive authority such as government contracting, civil rights enforcement, or antitrust action. A president’s pen alone cannot create a robust or dynamic accountability infrastructure for the technology industry. Nor can we rely on agencies to hold the line; recent Supreme Court decisions—Loper Bright, Corner Post, and others—have weakened their authority to use their mandated powers to adapt to new developments.

This, of course, is the more fundamental shortcoming of Biden’s progress on AI and technology governance: It does not carry the force of legislation. Without an accompanying push in Congress to counter such proposed rollbacks with new law, the United States will continue to embrace a largely ungoverned, innovation-at-all-costs technology landscape, with disparate state laws as the primary bulwark—and will continue to see the drift of emerging technologies away from the norms of robust democratic practice.

Yet meaningful governance efforts may be dead on arrival in a Congress that continues to embrace the flawed argument that without carte blanche for companies to “move fast and break things,” the United States would be doomed to lose to China, on both economic and military fronts. Such an approach cedes the AI competition to China’s terms, playing on the field of Chinese human rights violations and widespread surveillance instead of the field of American values and democratic practice. It also surrenders the U.S. security edge, enabling systems that could break or fail at any moment because they were rushed to market in the name of great-power competition.

Pursuing meaningful AI governance is a choice. So is the decision, over decades, to leave powerful data-centric technologies ungoverned—a decision to allow an assault on the rights, freedoms, and opportunities of many in American society. There is another path.

Washington has the opportunity to build a new, enduring paradigm in which the governance of data-centric predictive technologies, as well as the industry that creates them, is a core component of a robust U.S. democracy.

We must waste no time reaffirming that the protections afforded by previous generations of laws also apply to emerging technology. For the executive branch, this will require a landmark effort to ensure protections are robustly enforced in the digital sphere, expanding enforcement capacity in federal agencies with civil rights offices and enforcement mandates and keeping up the antitrust drumbeat that has put anti-competitive actors on notice.

The most consequential responsibility for AI governance, though, rests with Congress. Across the country, states are moving to pass laws on AI, many of which will contradict one another and form an overlapping legal tangle. Federal lawmakers should act in the tradition of the 1964 Civil Rights Act, issuing blanket protections for all Americans. At a minimum, this should include a new liability regime and guarantee protection from algorithmic discrimination; mandate pre- and post-deployment testing, transparency, and explainability of AI systems; and a requirement for developers of AI systems to uphold a duty of care, with the responsibility to ensure that systems are safe and effective.

These AI systems are powered by data, so such a bill should be accompanied by comprehensive data privacy protections, including a robust embrace of data minimization, barring companies from using personal information collected for one purpose in order to achieve an unrelated end.

While only a start, these steps to protect democratic practice in the age of AI would herald the end of America’s permissive approach to the technology sector’s harms and mark the beginning of a new democratic paradigm. They should be followed forcefully by a separate but complementary project: ensuring that individuals and communities participate in deciding how AI is used in their lives—and how it is not. Most critically, more workers—once called America’s “arsenal of democracy”—must organize and wield their collective power to bargain over whether, when, and how technologies are used in the workplace.

Such protections must also extend beyond the workplace into other areas of daily life where technology is used to shape important decisions. At a moment of weakening democratic norms, we need a new, concerted campaign to ease the path for anyone to challenge unfair decisions made about them by ungoverned AI systems or opt out of AI systems’ use altogether. This must include a private right of action for ordinary people who can show that AI has been used to break the law or violate their rights. We must also open additional pathways to individual and collective contestation, including robust, well-resourced networks of legal aid centers trained in representing low-income clients experiencing algorithmic harms.

We can bring many more people into the process of deciding what kinds of problems powerful AI systems are used to solve, from the way we allocate capital to the way we conduct AI research and development. Closing this gap requires allowing people across society to use AI for issues that matter to them and their communities. The federal government’s program to scale up access to public research, computing power, and data infrastructure is still only a pilot, and Congress has proposed to fund it at only $2.6 billion in its first six years. To grasp that number’s insufficiency, one needed only to listen to Google’s spring earnings call, where investors heard that the tech giant planned to spend about $12 billion on AI development per quarter. Next, the U.S. government should invest in the human and tech infrastructures of “public AI,” to provide both a sandbox for applied innovation in the public interest and a countervailing force to the concentration of economic and agenda-setting power in the AI industry.

These are some of the measures the United States can undertake to govern these new technologies. Even in an administration that broadly supports these goals, however, none of this will be possible or politically viable without a change in the overall balance of power. A broad-based, well-funded, and well-organized political movement on technology policy issues is needed to dramatically expand the coalition of people interested and invested in technology governance in the United States.

Ushering in these reforms begins with telling different stories to help people recognize their stake in these issues and understand that AI tools directly impact their access to quality housing, education, health care, and economic opportunity. This awareness must ultimately translate to pressure on lawmakers, a tool those standing in the way of a democratic vision for AI use to great effect. Musk is reportedly bankrolling a pro-Trump super PAC to the tune of tens of millions per month. Andreessen Horowitz, the venture firm led by anti-regulation founders, increased its lobbying budget between the first and second quarter of this year by 135 percent. Not only are the big corporate tech players spending millions of dollars on lobbying per quarter, but each is also running a political operation, spending big money to elect political candidates who will look after their interests.

The academic, research, and civil society actors whose work has helped change the tech policy landscape have succeeded in building strong policy and research strategies. Now is the time to venture further into the political battlefield and prepare the next generation of researchers, policy experts, and advocates to take up the baton. This will require new tools, such as base-building efforts with groups across the country that can help tie technology governance to popular public issues, and generational investments in political action committees and lobbying. This shift in strategy will require new, significant money; philanthropic funders who have traditionally backed research and nonprofit advocacy will need to also embrace an explicitly political toolkit.

The public interest technology movement urgently needs a political architecture that can at last impose a political cost on lawmakers who allow the illiberal shift of technology companies to proceed unabated. In the age of AI, the viability of efforts to protect democratic representation, practice, and norms may well hinge on the force with which non-industry players choose to fund and build political power—and leverage it.

A choice confronts the United States as we face down AI’s threats to democratic practice, representation, and norms. We can default to passivity, or we can use these instruments to shape a free society for the modern era. The decision is ours to make.

[cybonetictechnologiespvtltd]

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[cerastes]

Reed the Flame Shadow has allowed for a lot of creative plays, she’s truly fun to use. I also appreciate that she’s very versatile and that her skill selection is very case to case basis, like Cantabile for example. Both S2 and S3 have a lot of different roles and applications besides their main apparent slotted duties. S2 is her most damaging skill, though also her most resource-intensive skill if the aim is to use it for single target shredding (three deployment slots! Congruent with Kal’tsit, who needs two to do her huge damage — I like this idea of Medics that can theoretically deal a lot of damage but are expensive to use in the terms of slots), but even if you don’t want to use it like that, it’s still an immensely useful skill to lane, sustain and dps.

Likewise, S3 is famous for its big explosions and crowd thinning, but it’s not bad at all when you need a mix of mob control and boss/elite killing power. In IS3 Waves 12, for instance, the ATK debuff in Cinders has actually been very useful to survive some hits that my units otherwise would’ve buckled under, and the fact that it’s multitarget with a decent ATK buff means that Reed will be doling out insane healing in addition to good damage. I keep seeing this aspect of the skill glossed over, it’s an incredibly powerful sustain tool in addition to a damage tool, Cinders also inflict Arts Fragile, which stacks multiplicatively (to my knowledge) with Fragile, so a combo with Suzuran, Shamare, Pramanix and Gnosis can set up some truly delirious Arts haymakers on enemies.

Flame Shadow does so much for a single slot, with varied selection! She’s become core in my teams now. Part of that is my bias since she’s a favorite, but the other part is raw utilitarian pragmatism since she is honestly that good. Funnily enough, her S2 suffers from a similar issue as Laurentina’s S3: It’s description is not quite effective at explaining exactly how strong the skill really is.

[generouslywanderingpriest]

Video Agent: The Future of AI-Powered Content Creation

The rise of AI-generated content has transformed how businesses and creators produce videos. Among the most innovative tools is the video agent, an AI-driven solution that automates video creation, editing, and optimization. Whether for marketing, education, or entertainment, video agents are redefining efficiency and creativity in digital media.

In this article, we explore how AI-powered video agents work, their benefits, and their impact on content creation.

What Is a Video Agent?

A video agent is an AI-based system designed to assist in video production. Unlike traditional editing software, it leverages machine learning and natural language processing (NLP) to automate tasks such as:

Scriptwriting – Generates engaging scripts based on keywords.

Voiceovers – Converts text to lifelike speech in multiple languages.

Editing – Automatically cuts, transitions, and enhances footage.

Personalization – Tailors videos for different audiences.

These capabilities make video agents indispensable for creators who need high-quality content at scale.

How AI Video Generators Work

The core of a video agent lies in its AI algorithms. Here’s a breakdown of the process:

1. Input & Analysis

Users provide a prompt (e.g., "Create a 1-minute explainer video about AI trends"). The AI video generator analyzes the request and gathers relevant data.

2. Content Generation

Using GPT-based models, the system drafts a script, selects stock footage (or generates synthetic visuals), and adds background music.

3. Editing & Enhancement

The video agent refines the video by:

Adjusting pacing and transitions.

Applying color correction.

Syncing voiceovers with visuals.

4. Output & Optimization

The final video is rendered in various formats, optimized for platforms like YouTube, TikTok, or LinkedIn.

Benefits of Using a Video Agent

Adopting an AI-powered video generator offers several advantages:

1. Time Efficiency

Traditional video production takes hours or days. A video agent reduces this to minutes, allowing rapid content deployment.

2. Cost Savings

Hiring editors, voice actors, and scriptwriters is expensive. AI eliminates these costs while maintaining quality.

3. Scalability

Businesses can generate hundreds of personalized videos for marketing campaigns without extra effort.

4. Consistency

AI ensures brand voice and style remain uniform across all videos.

5. Accessibility

Even non-experts can create professional videos without technical skills.

Top Use Cases for Video Agents

From marketing to education, AI video generators are versatile tools. Key applications include:

1. Marketing & Advertising

Personalized ads – AI tailors videos to user preferences.

Social media content – Quickly generates clips for Instagram, Facebook, etc.

2. E-Learning & Training

Automated tutorials – Simplifies complex topics with visuals.

Corporate training – Creates onboarding videos for employees.

3. News & Journalism

AI-generated news clips – Converts articles into video summaries.

4. Entertainment & Influencers

YouTube automation – Helps creators maintain consistent uploads.

Challenges & Limitations

Despite their advantages, video agents face some hurdles:

1. Lack of Human Touch

AI may struggle with emotional nuance, making some videos feel robotic.

2. Copyright Issues

Using stock footage or AI-generated voices may raise legal concerns.

3. Over-Reliance on Automation

Excessive AI use could reduce creativity in content creation.

The Future of Video Agents

As AI video generation improves, we can expect:

Hyper-realistic avatars – AI-generated presenters indistinguishable from humans.

Real-time video editing – Instant adjustments during live streams.

Advanced personalization – AI predicting viewer preferences before creation.

[omgmaxsmith-blog]

Can Open Source Integration Services Speed Up Response Time in Legacy Systems?

Legacy systems are still a key part of essential business operations in industries like banking, logistics, telecom, and manufacturing. However, as these systems get older, they become less efficient—slowing down processes, creating isolated data, and driving up maintenance costs. To stay competitive, many companies are looking for ways to modernize without fully replacing their existing systems. One effective solution is open-source integration, which is already delivering clear business results.

Why Faster Response Time Matters

System response time has a direct impact on business performance. According to a 2024 IDC report, improving system response by just 1.5 seconds led to a 22% increase in user productivity and a 16% rise in transaction completion rates. This means increased revenue, customer satisfaction as well as scalability in industries where time is of great essence.

Open-source integration is prominent in this case. It can minimize latency, enhance data flow and make process automation easier by allowing easier communication between legacy systems and more modern applications. This makes the systems more responsive and quick.

Key Business Benefits of Open-Source Integration

Lower Operational Costs

Open-source tools like Apache Camel and Mule eliminate the need for costly software licenses. A 2024 study by Red Hat showed that companies using open-source integration reduced their IT operating costs by up to 30% within the first year.

Real-Time Data Processing

Traditional legacy systems often depend on delayed, batch-processing methods. With open-source platforms using event-driven tools such as Kafka and RabbitMQ, businesses can achieve real-time messaging and decision-making—improving responsiveness in areas like order fulfillment and inventory updates.

Faster Deployment Cycles: Open-source integration supports modular, container-based deployment. The 2025 GitHub Developer Report found that organizations using containerized open-source integrations shortened deployment times by 43% on average. This accelerates updates and allows faster rollout of new services.

Scalable Integration Without Major Overhauls

Open-source frameworks allow businesses to scale specific parts of their integration stack without modifying the core legacy systems. This flexibility enables growth and upgrades without downtime or the cost of a full system rebuild.

Industry Use Cases with High Impact

Banking

Integrating open-source solutions enhances transaction processing speed and improves fraud detection by linking legacy banking systems with modern analytics tools.

Telecom

Customer service becomes more responsive by synchronizing data across CRM, billing, and support systems in real time.

Manufacturing

Real-time integration with ERP platforms improves production tracking and inventory visibility across multiple facilities.

Why Organizations Outsource Open-Source Integration

Most internal IT teams lack skills and do not have sufficient resources to manage open-source integration in a secure and efficient manner. Businesses can also guarantee trouble-free setup and support as well as improved system performance by outsourcing to established providers. Top open-source integration service providers like Suma Soft, Red Hat Integration, Talend, TIBCO (Flogo Project), and Hitachi Vantara offer customized solutions. These help improve system speed, simplify daily operations, and support digital upgrades—without the high cost of replacing existing systems.

[niotechone]

Cloud Computing: Definition, Benefits, Types, and Real-World Applications

In the fast-changing digital world, companies require software that matches their specific ways of working, aims and what their customers require. That’s when you need custom software development services. Custom software is made just for your organization, so it is more flexible, scalable and efficient than generic software.

What does Custom Software Development mean?

Custom software development means making, deploying and maintaining software that is tailored to a specific user, company or task. It designs custom Software Development Services: Solutions Made Just for Your Business to meet specific business needs, which off-the-shelf software usually cannot do.

The main advantages of custom software development are listed below.

1. Personalized Fit

Custom software is built to address the specific needs of your business. Everything is designed to fit your workflow, whether you need it for customers, internal tasks or industry-specific functions.

2. Scalability

When your business expands, your software can also expand. You can add more features, users and integrations as needed without being bound by strict licensing rules.

3. Increased Efficiency

Use tools that are designed to work well with your processes. Custom software usually automates tasks, cuts down on repetition and helps people work more efficiently.

4. Better Integration

Many companies rely on different tools and platforms. You can have custom software made to work smoothly with your CRMs, ERPs and third-party APIs.

5. Improved Security

You can set up security measures more effectively in a custom solution. It is particularly important for industries that handle confidential information, such as finance, healthcare or legal services.

Types of Custom Software Solutions That Are Popular

CRM Systems

Inventory and Order Management

Custom-made ERP Solutions

Mobile and Web Apps

eCommerce Platforms

AI and Data Analytics Tools

SaaS Products

The Process of Custom Development

Requirement Analysis

Being aware of your business goals, what users require and the difficulties you face in running the business.

Design & Architecture

Designing a software architecture that can grow, is safe and fits your requirements.

Development & Testing

Writing code that is easy to maintain and testing for errors, speed and compatibility.

Deployment and Support

Making the software available and offering support and updates over time.

What Makes Niotechone a Good Choice?

Our team at Niotechone focuses on providing custom software that helps businesses grow. Our team of experts works with you throughout the process, from the initial idea to the final deployment, to make sure the product is what you require.

Successful experience in various industries

Agile development is the process used.

Support after the launch and options for scaling

Affordable rates and different ways to work together

Final Thoughts

Creating custom software is not only about making an app; it’s about building a tool that helps your business grow. A customized solution can give you the advantage you require in the busy digital market, no matter if you are a startup or an enterprise.