#advanced cloud computing training

[khayalonsebunealfaz]

[cupuletrainings]

Top Institutes for Website Design Training in Gwalior – CupuleTrainings

Cupule Trainings, as a best IT training institute in Gwalior, offers job consultancy service, certification and training in Angular Js, Android, Java, PHP, HTML5 Bootstrap, digital marketing, SEO, Social media marekting, Wordpress, Shopify, HTML CSS, CSS3, IOS, Web design and development, programming languages, database management system and all other certification courses from highly experienced industry experts.

[strategiadvizo]

Elevating Employability: Short-Term Course Suggestions for College Students

Empower your future with our latest blog on short-term courses for college students! 🚀 Enhance your employability and unlock new opportunities. Dive in to discover courses that fit your passion and career goals. #EmpowermentThroughEducation #SkillUp

“विद्या ददाति विनयं, विनयाद् याति पात्रताम्।” “Education bestows humility, humility leads to worthiness.” In a world that’s constantly evolving, the importance of education—especially for students from lesser-known colleges in India—cannot be overstated. Education not only paves the way for personal growth but also significantly boosts employability in today’s competitive job market. Here are…

[c1qfxugcgy0]

adventures in QA

(previous post in this series)

My shop in Advanced Midbody - Carbon Wing (AMCW) at Large Aircraft Manufacturer (LAM) is at the very end of the composite fabrication building. Hundreds of people carefully lay up a hundred foot long slab of carbon fiber, cure it, paint it, and then we totally fuck it up with out of spec holes, scrapes, primer damage, etc. The people who write up our many defects are from the Quality Assurance (QA) department.

Every single screw and rivet on a LAM aircraft can be traced back to the mechanic who installed it. Back when even everything was done in pen and pencil, it was joked that the paper used to produce an aircraft outweighed the plane itself. Now that everything is computer-based, of course, the amount of paperwork is free to grow without limit.

(Haunting the factory is endless media coverage of an emergency exit door plug popping out of an Advanced Smallbody - Upengine (ASU) plane during a routine flight a few months ago. Unlike that airframe's notorious problems with MCAS, this was a straightforward paperwork screwup by a line worker: the bolts were supposed to be tightened, and they weren't.

As a result the higher ups have visited hideous tribulations on non-salaried workers. Endless webinars, structured trainings. Here at the Widebody plant we have received a steady flow of refugees from the Narrowbody factory, hair-raising tales of receiving one hundred percent supervision from the moment they clock in to the second they clock out from FAA inspectors who can recommend actual jail time for any lapse in judgement.)

A single hydraulic bracket Installation Plan (IP) is around four brackets. The team leads generally assign two bracket IPs per mechanic, since each bracket set is something like a foot apart, and while working on the plane is bad enough it's much worse to have another mechanic in your lap.

Let me list the order of operations:

One: Find where you're supposed to install these brackets. This is harder than you might think.

Firstly, it's a hundred foot long plank of carbon fiber composite, with longitudinal stringers bonded to it to add stiffness. The stringers are pilot drilled in the trim and drill center, a truly Brobdingnagian CNC mill that trims off the composite flash at the edges and locates and drills part holes for us. But there's a lot of holes, so you must carefully find your set.

A minor difficulty is that the engineering drawings are laid out with the leading edge pointing up, while the wing panels in our cells hang from the trailing edge. Not so bad, you just rotate the paper 180 when orienteering, then rotate it back up to read the printed labels.

A major difficulty is that the drawings are from the perspective from the outside of the panel. But we work on the inside of the wing (obviously, that's where all the parts are installed) so we also flip the drawings and squint through the back of the paper, to make things line up.

Large Aircraft Manufacturer has a market cap of US$110 billion, and we're walking around the wing jig with sheets of paper rotated 180 and flipped turnways trying to find where to put brackets.

Oh well, we're paid by the hour.

Two: Match drill the aluminum brackets to the carbon fiber composite stringer. I can devote an entire post to the subtleties of drilling carbon fiber, but I can already tell that this post is going to be a miserable slog, so I will merrily skip over this step.

Three: Vacuum up all the carbon dust and aluminum swarf created during this process. This step is not optional, as your team lead will remind you, his screaming mouth clouding your safety glasses with spittle at a distance of four inches. LAM is very serious about FOD. Every jet airliner you've ever ridden in is a wet wing design-- each interstitial space is filled with Jet A. There is no fuel bladder or liner-- the fuel washes right over plane structure and wing hardware. Any dirt we leave behind will merrily float into the fuel and be sucked right into the engines, where it can cause millions in damage. No place for metal shavings!

If you are nervous about flying, avoid considering that all the hydraulic lines and engine control cables dip into a lake of a kerosene on their way from the flight deck to the important machines they command. Especially do not consider that we're paid about as much per hour as a McDonalds fry cook to install flight-critical aviation components.

Four: Neatly lay out your brackets on your cart, fight for a position at a Shared Production Workstation (SPW) (of which we have a total of four (4) for a crew of thirty (30) mechanics) and mark your IP for QA inspection as Ready To Apply Seal.

Four: Twiddle your thumbs. Similarly, we have three QA people for thirty mechanics. This is not enough QA people, as I will make enormously clear in the following steps.

Five: Continue waiting. Remember, you must not do anything until a QA person shows up and checks the box. Skipping a QA step is a “process failure” and a disciplinary offense. From the outside, you can observe the numerous QA whistleblowers and say “golly, why would a mechanic ever cut a corner and ignore QA?” Well...

Six: QA shows up. Theoretically, they could choose to pick up the mahrmax you prepared for them and gauge every single hole you've drilled. But since we're three hours into the shift and they're already twenty jobs behind, they just flick their flashlight across the panel and say “looks good" and then sprint away. Can't imagine why our planes keep falling out of the sky.

Seven: Apply the seal to the bracket. P/S 890 is a thick dark gray goop that adheres well to aluminum, carbon fiber, fabric, hair and skin. Once cured, it is completely immune to any chemical attack short of piranha solution, so if you get any on yourself you had better notice quick, otherwise it'll be with you as long as the layer of epidermis it's bonded to. LAM employees who work with fuel tank sealant very quickly get out of the habit of running their hands through their hair.

Eight: Now you wait again. Ha ha, you dumb asshole, you thought you were done with QA? No no, now you put up the job for QA inspection of how well you put the seal on the bracket. Twiddle your thumbs, but now with some urgency. The minute you took the bottle of seal out of the freezer, you started the clock on its "squeeze-out life." For this type of seal, on this job, it's 120 minutes. If QA doesn't get to you before that time expires, you remove your ticket, wipe off the seal, take another bottle out the freezer, and apply a fresh layer.

Nine: Optimistically, QA shows up in time and signs off on the seal. Well, you're 100 minutes into your 120 minute timer. Quickly, you slap the brackets onto the stringer, air hammer the sleeve bolts into position, thread nuts onto the bolts, then torque them down. Shove through the crowd and mark your IP "ready to inspect squeeze out"

Ten: Let out a long breath and relax. All the time sensitive parts are over. The criteria here is "visible and continuous" squeeze out all along the perimeter of the bracket and the fasteners. It is hard to screw this up, just glop on a wild excess of seal before installing it. If you do fail squeezeout, though, the only remedy is to take everything off, throw away the single-use distorted thread locknuts, clean everything up and try again tomorrow.

Eleven: QA approved squeeze out? Break's over, now we're in a hurry again. By now there's probably only an hour or two left in the shift, and your job now is to clean off all that squeeze out. Here's where you curse your past self for glopping on too much seal. You want to get it off ASAP because if you leave it alone or if it's too late in the shift and your manager does feel like approving overtime it'll cure to a rock hard condition overnight and you'll go through hell chipping it off the next day. You'll go through a hundred or so qtips soaked in MPK cleaning up the bracket and every surface of the panel within three feet.

Twelve: Put it up for final inspection. Put away all your tools. (The large communal toolboxes are lined with kaizen foam precisely cut out to hold each individual tool, which makes it obvious if any tool is missing. When you take a tool out, you stick a tool chit with your name and LAMID printed on it in its place. Lose a tool? Stick your head between your legs and kiss your ass goodbye, pal, because the default assumption is that a lost screwdriver is lurking in a hollow "hat" stringer, waiting to float out and damage some critical component years after the airplane is delivered.)

One tool you'll leave on your cart, however, is the pin protrusion gage. There is a minimum amount of thread that must poke outside of the permanent straight shank fastener's (Hi-Lok) nut, to indicate that the nut is fully engaged. That makes sense. But there's also a maximum protrusion. Why?

Well, it's an airplane. Ounces make pounds. An extra quarter inch of stickout across a thousand fasteners across a 30 year service life means tons of additional fuel burnt. So you can't use a fastener that's too long, because it adds weight.

On aluminum parts, it's hard to mess up. But any given composite part is laid up from many layers of carbon fiber tape. The engineers seemed to have assumed that dimensional variation would be normally distributed. But, unfortunately, we buy miles of carbon fiber at a time, and the size only very gradually changes between lots. When entire batches are several microns oversize, and you're laying up parts from fifty plies and an inch thick, you can have considerable variation of thickness on any given structural component. So you had better hope you had test fit all of your fasteners ahead of time, or else you'll be real sorry!

And, if you're really lucky, QA will show up five minutes before end of shift, pronounce everything within tolerance, then fuck off.

And that's how it takes eight hours to install eight brackets.

[darkficsyouneveraskedfor]

Sunshine, Lollipops, and Rainbows 2

Warnings: non/dubcon, clashing personalities, exclusion, and other dark elements. My username actually says you never asked for any of this.

Characters: moody boy Curtis Everett x bubbly, plus-size reader

My warnings are not exhaustive but be aware this is a dark fic and may include potentially triggering topics. Please use your common sense when consuming content. I am not responsible for your decisions.

As usual, I would appreciate any and all feedback. I’m happy to once more go on this adventure with all of you! Thank you in advance for your comments and for reblogging.

Your second day isn’t as intimidating. You find your desk by yourself and even remembered your honey bear mug! You tuck your bag underneath as your computer boots and check your phone for any updates from your blog. Nothing special, just a hobby.

You yawn and sign in, taking two tries to remember your credentials correctly. You check the shared calendar and see that you have a meeting after lunch with IT. Daniella mentioned you had to get your security passes before the end of the week, that’s probably what that’s for.

You swivel back and forth as you open up your training list. You’re making good progress. You think. You don’t really know. It seems like a lot and despite feeling as if you’ve run a marathon, there are only a few ticks marked off.

Before you dive in, you need a pick-me-up. You really liked that butterscotch coffee but you might try something new. You enter the kitchen and wait behind a woman you don’t know as she brews her coffee. When she’s done, she returns your ‘good morning’ but doesn’t stop to chat. Must be a busy day.

You place your cup on the tray and pick out a French Vanilla pod. You don’t really know what the difference between regular vanilla and French vanilla is. Maybe the French stuff is fancy. Ooh la la.

You hum as the coffee grinds. It sounds angry. Well, it is probably the most overworked fellow in this place. Every day, seeing the heart caffeine hounds, having them poke his face, and glare until he does his jobs.

It’s a machine. Your mother always said you put a bit too much empathy into objects without sentience. Well, your English teacher shouldn’t have made you read that book about Electric Sheep or whatever.

Your cup is full and you grab it, focused on putting the lid on it to keep it nice and warm. As you turn, you fail to stop in time. Your hand knocks against the man’s chest and you gasp as coffee splashes onto his dark shirt. Not much as you manage to block most of it but enough to make him grunt and step back.

It’s him! Oh no. You’ve upset him again.

“I’m sorry, mister,” you say as you hold out your dripping cup, “I didn’t hear you. You sure are quiet.”

He grumbles and stomps to the sink, slamming his mug down as he snatches paper towels from the dispenser. You bite your lip nervously and near. You keep your cup from dripping onto your light blue cardigan with the little white clouds.

“Can I have some–”

He wipes his hands and shirt with a growl. He swipes up his cup without and answer and moves around you to the coffee machine. His cup hits the tray hard and he jabs the screen as it beeps at him in demand of a pod. He takes one and peels open the package before shoving it inside.

“I’m really sorry,” you say as you dry off your cup and fix the lid firmly, “you snuck up on me… like a wolf.”

He shakes his head and looks at the ceiling. He’s tall, his posture is straight and unbending, making you more conscious of your slouching. He wears all black that day, it makes him look lean, and the silver rings shine around his fingers. You only then notice the stud in his ear.

“Oh! I like your earring–”

“Why are you talking to me?” He snarls without looking at you.

You recoil and sputter. You’re not being rude. You’re just trying to be nice. He reminds you of that guy in university who used to call you airhead.

“Because… I wanna?” You say with a shrug, “I still didn’t get your name.”

“Look, I’m not interested in making friends. I come in,” he takes his cup from the tray, “do my work,” he points at you past the porcelain, “and I mind my goddamn business.”

He turns and strides out, another beastly sneer rolling out of him. You furrow your brow and pout at the door. Tammy enters with her own mug, a bright pink thing with a picture of Dolly Parton on it. Ah, you get it, 9-5.

“Ugh, that man is always in a mood,” she says.

“Yeah…” you agree thinly.

“Try not to get in his way. Five years and he’s never said a word to me. It’s too bad, he’s not bad on the eyes.”

You don’t acknowledge her last sentence. It’s not very appropriate for the workplace and she’s married. Quite happily as she only ever talks about her husband. You tell her to enjoy her coffee and go back to your desk.

Maybe you should just steer clear. Eat at your desk or somewhere else.

[dertaglichedan]

Cloud and AI are ‘fundamentally changing’ ability to forecast weather, NOAA chief says

LAS VEGAS — National Oceanic and Atmospheric Administration head Rick Spinrad said this week that even as hurricanes, wildfires and other weather events worsen, the use of innovative tech like cloud computing and AI is improving the agency’s ability to predict and forecast them.

“This is fundamentally changing our ability to do probably the most important thing in our business, and that's predict, project and forecast,” said Spinrad, speaking at AWS’ re:Invent 2024 conference in Las Vegas.

Spinrad said NOAA, which houses the National Weather Service and owns or operates 18 weather satellites, archives about 230 terabytes of environmental data per month from various observational platforms, ranging from the sea, to ships and even space.

That data is then hosted by commercial cloud service providers and made available to the public and nascent climate industry through NOAA’s Open Data Dissemination program, or NODD. AWS, Spinrad said, now hosts 32 petabytes of environmental information, or about “half of [NOAA’s] holdings.”

“Our ability to collect these data, put them on NODD, store them in a system that allows AI applications, is really critical,” Spinrad said. “And it's not just for our use at NOAA. We are supporting a burgeoning climate industrial effort, a commercial weather enterprise. We are now collecting enough environmental information — enough environmental intelligence — to make a fundamental difference.”

According to Spinrad, the difference includes improved access to critical weather data for incident meteorologists in the field. Using another tool from Amazon, AppStream 2.0, incident meteorologists dispatched to the scenes of floods, droughts, storms and wildfires can “have the same kind of access to our advanced weather information and interactive processing system that they would back at the home office.”

Spinrad said forecasters have been able to make a “seven year advancement in forecast capability in a matter of months using AI, using the training data [NOAA] now has access to.” Such advancements would not be possible without the ability to assimilate new data types, he added, noting that autonomous systems, satellites and surface-based robots all provide data that can go into forecasts.

[tenderlycloudymeteor]

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Introduction

In the rapidly evolving world of technology, the spotlight often shines on processors—those little chips that power everything from laptops to supercomputers. However, as we delve deeper into the realms of artificial intelligence (AI) and quantum computing, it becomes increasingly clear that innovation goes far beyond just raw processing power. Intel, a cornerstone of computing innovation since its inception, is at the forefront of these technological advancements. This article aims to explore Intel's innovations in AI and quantum computing, examining how these developments are reshaping industries and our everyday lives.

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Intel has long been synonymous with microprocessors, but its vision extends well beyond silicon. With an eye on future technologies like AI and quantum computing, Intel is not just building faster chips; it is paving the way click here for entirely new paradigms in data processing.

Understanding the Landscape of AI

Artificial Intelligence (AI) refers to machines' ability to perform tasks that typically require human intelligence. These tasks include visual perception, speech recognition, decision-making, and language translation.

The Role of Machine Learning

Machine learning is a subset of AI that focuses on algorithms allowing computers to learn from data without explicit programming. It’s like teaching a dog new tricks—through practice and feedback.

Deep Learning: The Next Level

Deep learning takes machine learning a step further using neural networks with multiple layers. This approach mimics human brain function and has led to significant breakthroughs in computer vision and natural language processing.

Intel’s Approach to AI Innovation

Intel has recognized the transformative potential of AI and has made significant investments in this area.

AI-Optimized Hardware

Intel has developed specialized hardware such as the Intel Nervana Neural Network Processor (NNP), designed specifically for deep learning workloads. This chip aims to accelerate training times for neural networks significantly.

Software Frameworks for AI Development

Alongside hardware advancements, Intel has invested in software solutions like the OpenVINO toolkit, which optimizes deep learning models for various platforms—from edge devices to cloud servers.

Applications of Intel’s AI Innovations

The applications for Intel’s work in AI are vast and varied.

Healthcare: Revolutionizing Diagnostics

AI enhances diagnostic accuracy by analyzing medical images faster than human radiologists. It can identify anomalies that may go unnoticed, improving patient outcomes dramatically.

Finance: Fraud Detection Systems

In finance, AI algorithms can scan large volumes of transactions in real-time to flag suspicious activity. This capability not only helps mitigate fraud but also accelerates transaction approvals.

Quantum Computing: The New Frontier

While traditional computing relies on bits (0s and 1s), quantum computing utilizes qubits that can exist simultaneously in multiple states—allowing for unprecede

[equallyfantasticsquadron]

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Introduction

In the rapidly evolving world of technology, the spotlight often shines on processors—those little chips that power everything from laptops to supercomputers. However, as we delve deeper into the realms of artificial intelligence (AI) and quantum computing, it becomes increasingly clear that innovation goes far beyond just raw processing power. Intel, a cornerstone of computing innovation since its inception, is at the forefront of these technological advancements. This article aims to explore Intel's innovations in AI and quantum computing, examining how these developments are reshaping industries and our everyday lives.

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Intel has long been synonymous with microprocessors, but its vision extends well beyond silicon. With an eye on future technologies like AI and quantum computing, Intel is not just building faster chips; it is paving the way for entirely new paradigms in data processing.

Understanding the Landscape of AI

Artificial Intelligence (AI) refers to machines' ability to perform tasks that typically require human intelligence. These tasks include visual perception, speech recognition, decision-making, and language translation.

The Role of Machine Learning

Machine learning is a subset of AI that focuses on algorithms allowing computers to learn from data without explicit programming. It’s like teaching a dog new tricks—through practice and feedback.

Deep Learning: The Next Level

Deep learning takes machine learning a step further using neural networks with multiple layers. This approach mimics human brain function and has led to significant breakthroughs in computer vision and natural language processing.

Intel’s Approach to AI Innovation

Intel has recognized the transformative potential of AI and has made significant investments in this area.

AI-Optimized Hardware

Intel has developed specialized hardware such as the Intel Nervana Neural Network Processor (NNP), designed specifically for deep learning workloads. This chip aims to accelerate training times for neural networks significantly.

Software Frameworks for AI Development

Alongside hardware Click to find out more advancements, Intel has invested in software solutions like the OpenVINO toolkit, which optimizes deep learning models for various platforms—from edge devices to cloud servers.

Applications of Intel’s AI Innovations

The applications for Intel’s work in AI are vast and varied.

Healthcare: Revolutionizing Diagnostics

AI enhances diagnostic accuracy by analyzing medical images faster than human radiologists. It can identify anomalies that may go unnoticed, improving patient outcomes dramatically.

Finance: Fraud Detection Systems

In finance, AI algorithms can scan large volumes of transactions in real-time to flag suspicious activity. This capability not only helps mitigate fraud but also accelerates transaction approvals.

Quantum Computing: The New Frontier

While traditional computing relies on bits (0s and 1s), quantum computing utilizes qubits that can exist simultaneously in multiple states—allowing for unprecede

[buysellram]

KIOXIA Unveils 122.88TB LC9 Series NVMe SSD to Power Next-Gen AI Workloads

KIOXIA America, Inc. has announced the upcoming debut of its LC9 Series SSD, a new high-capacity enterprise solid-state drive (SSD) with 122.88 terabytes (TB) of storage, purpose-built for advanced AI applications. Featuring the company’s latest BiCS FLASH™ generation 8 3D QLC (quad-level cell) memory and a fast PCIe® 5.0 interface, this cutting-edge drive is designed to meet the exploding data demands of artificial intelligence and machine learning systems.

As enterprises scale up AI workloads—including training large language models (LLMs), handling massive datasets, and supporting vector database queries—the need for efficient, high-density storage becomes paramount. The LC9 SSD addresses these needs with a compact 2.5-inch form factor and dual-port capability, providing both high capacity and fault tolerance in mission-critical environments.

Form factor refers to the physical size and shape of the drive—in this case, 2.5 inches, which is standard for enterprise server deployments. PCIe (Peripheral Component Interconnect Express) is the fast data connection standard used to link components to a system’s motherboard. NVMe (Non-Volatile Memory Express) is the protocol used by modern SSDs to communicate quickly and efficiently over PCIe interfaces.

Accelerating AI with Storage Innovation

The LC9 Series SSD is designed with AI-specific use cases in mind—particularly generative AI, retrieval augmented generation (RAG), and vector database applications. Its high capacity enables data-intensive training and inference processes to operate without the bottlenecks of traditional storage.

It also complements KIOXIA’s AiSAQ™ technology, which improves RAG performance by storing vector elements on SSDs instead of relying solely on costly and limited DRAM. This shift enables greater scalability and lowers power consumption per TB at both the system and rack levels.

“AI workloads are pushing the boundaries of data storage,” said Neville Ichhaporia, Senior Vice President at KIOXIA America. “The new LC9 NVMe SSD can accelerate model training, inference, and RAG at scale.”

Industry Insight and Lifecycle Considerations

Gregory Wong, principal analyst at Forward Insights, commented:

“Advanced storage solutions such as KIOXIA’s LC9 Series SSD will be critical in supporting the growing computational needs of AI models, enabling greater efficiency and innovation.”

As organizations look to adopt next-generation SSDs like the LC9, many are also taking steps to responsibly manage legacy infrastructure. This includes efforts to sell SSD units from previous deployments—a common practice in enterprise IT to recover value, reduce e-waste, and meet sustainability goals. Secondary markets for enterprise SSDs remain active, especially with the ongoing demand for storage in distributed and hybrid cloud systems.

LC9 Series Key Features

122.88 TB capacity in a compact 2.5-inch form factor

PCIe 5.0 and NVMe 2.0 support for high-speed data access

Dual-port support for redundancy and multi-host connectivity

Built with 2 Tb QLC BiCS FLASH™ memory and CBA (CMOS Bonded to Array) technology

Endurance rating of 0.3 DWPD (Drive Writes Per Day) for enterprise workloads

The KIOXIA LC9 Series SSD will be showcased at an upcoming technology conference, where the company is expected to demonstrate its potential role in powering the next generation of AI-driven innovation.

[lethalruinoracle]

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Introduction

In the rapidly evolving world of technology, the spotlight often shines on processors—those little chips that power everything from laptops to supercomputers. However, as we delve deeper into the realms of artificial intelligence (AI) and quantum computing, it becomes increasingly clear that innovation goes far beyond just raw processing power. Intel, a cornerstone of computing innovation since its inception, is at the forefront of these technological advancements. This article aims to explore Intel's innovations in AI and quantum computing, examining how these developments are reshaping industries and our everyday lives.

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Intel has long been synonymous with microprocessors, but its vision extends well beyond silicon. With an eye on future technologies like AI and quantum computing, Intel is not just building faster chips; it is paving the way for entirely new paradigms in data processing.

Understanding the Landscape of AI

Artificial Intelligence (AI) refers to machines' ability to perform tasks that typically require human intelligence. These tasks include visual perception, speech recognition, decision-making, and language translation.

Click here The Role of Machine Learning

Machine learning is a subset of AI that focuses on algorithms allowing computers to learn from data without explicit programming. It’s like teaching a dog new tricks—through practice and feedback.

Deep Learning: The Next Level

Deep learning takes machine learning a step further using neural networks with multiple layers. This approach mimics human brain function and has led to significant breakthroughs in computer vision and natural language processing.

Intel’s Approach to AI Innovation

Intel has recognized the transformative potential of AI and has made significant investments in this area.

AI-Optimized Hardware

Intel has developed specialized hardware such as the Intel Nervana Neural Network Processor (NNP), designed specifically for deep learning workloads. This chip aims to accelerate training times for neural networks significantly.

Software Frameworks for AI Development

Alongside hardware advancements, Intel has invested in software solutions like the OpenVINO toolkit, which optimizes deep learning models for various platforms—from edge devices to cloud servers.

Applications of Intel’s AI Innovations

The applications for Intel’s work in AI are vast and varied.

Healthcare: Revolutionizing Diagnostics

AI enhances diagnostic accuracy by analyzing medical images faster than human radiologists. It can identify anomalies that may go unnoticed, improving patient outcomes dramatically.

Finance: Fraud Detection Systems

In finance, AI algorithms can scan large volumes of transactions in real-time to flag suspicious activity. This capability not only helps mitigate fraud but also accelerates transaction approvals.

Quantum Computing: The New Frontier

While traditional computing relies on bits (0s and 1s), quantum computing utilizes qubits that can exist simultaneously in multiple states—allowing for unprecede

[thaiattorney]

Thailand SMART Visa

1.1 Statutory Foundations

Established under Royal Decree on SMART Visa B.E. 2561 (2018)

Amended by Ministerial Regulation No. 377 (2021) expanding eligible sectors

Operates within Thailand 4.0 Economic Model under BOI oversight

1.2 Governance Structure

Primary Authority: Board of Investment (BOI)

Interagency Coordination:

Immigration Bureau (visa issuance)

Digital Economy Promotion Agency (tech qualifications)

Ministry of Higher Education (academic validation)

Technical Review Committees:

12 sector-specific panels

Investment verification unit

2. Eligibility Criteria & Qualification Pathways

2.1 SMART-T (Experts)

Compensation Thresholds

Base Salary: Minimum THB 200,000/month (USD 5,800)

Alternative Compensation:

Equity valued at 25% premium

Performance bonuses (capped at 40% of base)

2.2 SMART-E (Entrepreneurs)

Startup Metrics

Revenue Test: THB 10M+ ARR

Traction Test: 50,000 MAU

Funding Test: Series A (THB 25M+)

Accelerator Requirements:

DEPA-certified programs

Minimum 6-month incubation

3. Application Process & Technical Review

3.1 Document Authentication Protocol

Educational Credentials:

WES/IQAS evaluation for foreign degrees

Notarized Thai translations (MFA-certified)

Employment Verification:

Social security cross-check

Three professional references

3.2 Biometric Enrollment

Facial Recognition: 12-point capture system

Fingerprinting: 10-print electronic submission

Iris Scanning: Optional for Diamond tier

4. Privilege Structure & Compliance

4.1 Employment Rights Framework

Permitted Activities:

Primary employment (≥80% time)

Academic collaboration (≤20%)

Advisory roles (max 2 concurrent)

Restrictions:

Local employment outside specialty

Political activities

Unapproved commercial research

4.2 Dependent Provisions

Spousal Work Rights:

General employment permitted

No industry restrictions

Child Education:

25% tuition subsidy

University admission priority

4.3 Mobility Features

Airport Processing:

Dedicated SMART lanes at 6 airports

15-minute clearance guarantee

Re-entry Flexibility:

Unlimited exits

72-hour grace period

5. Sector-Specific Implementations

5.1 Biotechnology

Special Privileges:

Lab equipment duty waivers

Fast-track FDA approval

50% R&D tax deduction

5.2 Advanced Manufacturing

Incentives:

Robotics import tax exemption

Industrial land lease discounts

THB 500K training subsidy

5.3 Digital Infrastructure

Cloud Computing:

VAT exemption on services

30% energy cost reduction

Cybersecurity:

Liability protections

Gov't certification fast-track

6. Compliance & Monitoring

6.1 Continuous Reporting

Quarterly:

Employment verification

Investment maintenance

Annual:

Contribution assessment

Salary benchmarking

6.2 Renewal Process

Documentation:

Updated financials

Health insurance (USD 100K)

Performance metrics

Fees:

THB 10,000 renewal

THB 1,900 visa stamp

7. Emerging Developments

71 2024 Enhancements

Blockchain Specialist Category

Climate Tech Fast-Track

EEC Regional Expansion

7.2 Pending Reforms

Dual Intent Provision

Skills Transfer Mandate

Global Talent Pool

8. Strategic Application Approach

8.1 Pre-Submission Optimization

Compensation Restructuring

Patent Portfolio Development

Professional Endorsements

8.2 Post-Approval Planning

Tax Residence Strategy

Asset Protection

Succession Planning

9. Risk Management

9.1 Common Rejection Reasons

Document Issues (32%)

Qualification Gaps (28%)

Financial Irregularities (19%)

9.2 Operational Challenges

Banking Restrictions

Healthcare Access

Cultural Integration

[attorneyssphuket]

Thailand SMART Visa

1.1 Statutory Foundations

Established under Royal Decree on SMART Visa B.E. 2561 (2018)

Amended by Ministerial Regulation No. 377 (2021) expanding eligible sectors

Operates within Thailand 4.0 Economic Model under BOI oversight

1.2 Governance Structure

Primary Authority: Board of Investment (BOI)

Interagency Coordination:

Immigration Bureau (visa issuance)

Digital Economy Promotion Agency (DEPA) for tech qualifications

Ministry of Higher Education for academic validation

Technical Review Committees:

Sector-specific panels (12 industries)

Investment verification unit

2. Eligibility Criteria & Qualification Pathways

2.1 SMART-T (Experts)

Compensation Thresholds

Base Salary: Minimum THB 200,000/month (USD 5,800)

Alternative Compensation:

Equity valued at 25% premium to cash salary

Performance bonuses (capped at 40% of base)

2.2 SMART-E (Entrepreneurs)

Startup Metrics

Revenue Test: THB 10M+ ARR

Traction Test: 50,000 MAU

Funding Test: Series A (THB 25M+)

Accelerator Requirements:

DEPA-certified programs

Minimum 6-month incubation

3. Application Process & Technical Review

3.1 Document Authentication Protocol

Educational Credentials:

WES/IQAS evaluation for foreign degrees

Notarized Thai translations (certified by MFA)

Employment Verification:

Social security cross-check (home country)

Three professional references (direct supervisors)

3.2 Biometric Enrollment

Facial Recognition: 12-point capture system

Fingerprinting: 10-print electronic submission

Iris Scanning: Optional for Diamond tier

4. Privilege Structure & Compliance

4.1 Employment Rights Framework

Permitted Activities:

Primary employment with sponsor (≥80% time)

Academic collaboration (≤20% time)

Advisory roles (max 2 concurrent)

Restrictions:

Local employment outside specialty

Political activities

Unapproved commercial research

4.2 Dependent Provisions

Spousal Work Rights:

General employment permitted

No industry restrictions

Child Education:

25% tuition subsidy at partner schools

University admission priority

4.3 Mobility Features

Airport Processing:

Dedicated SMART lanes at 6 airports

15-minute clearance guarantee

Re-entry Flexibility:

Unlimited exits

72-hour grace period

5. Sector-Specific Implementations

5.1 Biotechnology

Special Privileges:

Lab equipment duty waivers

Fast-track FDA approval

50% R&D tax deduction

5.2 Advanced Manufacturing

Incentives:

Robotics import tax exemption

Industrial land lease discounts

THB 500K training subsidy

5.3 Digital Infrastructure

Cloud Computing:

VAT exemption on services

30% energy cost reduction

Cybersecurity:

Liability protections

Gov't certification fast-track

6. Compliance & Monitoring

6.1 Continuous Reporting

Quarterly:

Employment verification

Investment maintenance

Annual:

Contribution assessment

Salary benchmarking

6.2 Renewal Process

Documentation:

Updated financials

Health insurance (USD 100K)

Performance metrics

Fees:

THB 10,000 renewal

THB 1,900 visa stamp

7. Emerging Developments

7.1 2024 Enhancements

Blockchain Specialist Category

Climate Tech Fast-Track

EEC Regional Expansion

7.2 Pending Reforms

Dual Intent Provision

Skills Transfer Mandate

Global Talent Pool

8. Strategic Application Approach

8.1 Pre-Submission Optimization

Compensation Restructuring

Patent Portfolio Development

Professional Endorsements

8.2 Post-Approval Planning

Tax Residence Strategy

Asset Protection

Succession Planning

9. Risk Management

9.1 Common Rejection Reasons

Document Issues (32%)

Qualification Gaps (28%)

Financial Irregularities (19%)

9.2 Operational Challenges

Banking Restrictions

Healthcare Access

Cultural Integration

[joanhermann]

The Role of CCNP in Multi-Cloud Networking

We live in a time where everything is connected—our phones, laptops, TVs, watches, even our refrigerators. But have you ever wondered how all this connection actually works? Behind the scenes, there are large computer networks that make this possible. Now, take it one step further and imagine companies using not just one but many cloud services—like Google Cloud, Amazon Web Services (AWS), and Microsoft Azure—all at the same time. This is called multi-cloud networking. And to manage this kind of advanced setup, skilled professionals are needed. That’s where CCNP comes in.

Let’s break this down in a very simple way so that even a school student can understand it.

What Is Multi-Cloud Networking?

Imagine you’re at a school event. You have food coming from one stall, water from another, and sweets from a third. Now, imagine someone needs to manage everything—make sure food is hot, water is cool, and sweets arrive on time. That manager is like a multi-cloud network engineer. Instead of food stalls, though, they're managing cloud services.

So, multi-cloud networking means using different cloud platforms to store data, run apps, or provide services—and making sure all these platforms work together without any confusion or delay.

So, Where Does CCNP Fit In?

CCNP, which stands for Cisco Certified Network Professional, teaches you how to build, manage, and protect networks at a professional level. If CCNA is the beginner level, CCNP is the next big step.

When we say someone has completed CCNP training, it means they’ve learned advanced networking skills—skills that are super important for multi-cloud setups. Whether it’s connecting a company’s private network to cloud services or making sure all their apps work smoothly between AWS, Azure, and Google Cloud, a CCNP-certified person can do it.

Why Is CCNP Important for Multi-Cloud?

Here are a few simple reasons why CCNP plays a big role in this new world of multi-cloud networking:

Connecting Different Platforms: Each cloud service is like a different language. CCNP helps you understand how to make them talk to each other.

Security and Safety: In multi-cloud networks, data moves in many directions. CCNP-certified professionals learn how to keep that data safe.

Speed and Performance: If apps run slowly, users get frustrated. CCNP training teaches you how to make networks fast and efficient.

Troubleshooting Problems: When something breaks in a multi-cloud system, it can be tricky to fix. With CCNP skills, you’ll know how to find the issue and solve it quickly.

What You Learn in CCNP That Helps in Multi-Cloud

Let’s look at some topics covered in CCNP certification that directly help with multi-cloud work:

Routing and Switching: This means directing traffic between different networks smoothly, which is needed in a multi-cloud setup.

Network Automation: You learn how to make systems work automatically, which is super helpful when managing multiple clouds.

Security: You’re trained to spot and stop threats, even if they come from different cloud platforms.

Virtual Networking: Since cloud networks are often virtual (not physical wires and cables), CCNP teaches you how to work with them too.

Can I Learn CCNP Online?

Yes, you can! Thanks to digital learning, you can take a CCNP online class from anywhere—even your home. You don’t need to travel or sit in a classroom. Just a good internet connection and the will to learn is enough.

An online class is perfect for students or working professionals who want to upgrade their skills in their free time. It also helps you learn at your own speed. You can pause, repeat, or review topics anytime.

What Happens After You Get Certified?

Once you finish your CCNP certification, you’ll find many doors open for you. Especially in companies that use multiple cloud platforms, your skills will be in high demand. You could work in roles like:

Cloud Network Engineer

Network Security Analyst

IT Infrastructure Manager

Data Center Specialist

And the best part? These roles come with good pay and long-term career growth.

Where Can I Learn CCNP?

You can take CCNP training from many places, but it's important to choose a center that gives you hands-on practice and teaches in simple language. One such place is Network Rhinos, which is known for making difficult topics easy to understand. Whether you’re learning online or in-person, the focus should always be on real-world skills, not just theory.

Final Thoughts

The world is moving fast toward cloud-based technology, and multi-cloud setups are becoming the new normal. But with more clouds come more challenges. That’s why companies are looking for smart, trained professionals who can handle the job.

CCNP training prepares you for exactly that. Whether you're just starting your career or want to move to the next level, CCNP gives you the skills to stay relevant and in demand.

With options like a CCNP online class, you don’t even have to leave your house to become an expert. And once you complete your CCNP certification, you're not just learning about networks—you’re becoming someone who can shape the future of cloud technology.

So yes, if you’re thinking about CCNP in a world that’s quickly moving to the cloud, the answer is simple: go for it.

[lovilove0808]

Breaking into Tech: How Linux Skills Can Launch Your Career in 2025

In today's rapidly evolving tech landscape, Linux skills have become increasingly valuable for professionals looking to transition into rewarding IT careers. As we move through 2025, the demand for Linux System Administrators continues to grow across industries, creating excellent opportunities for career changers—even those without traditional technical backgrounds.

Why Linux Skills Are in High Demand

Linux powers much of the world's technology infrastructure. From enterprise servers to cloud computing environments, this open-source operating system has become the backbone of modern IT operations. Organizations need skilled professionals who can:

Deploy and manage enterprise-level IT infrastructure

Ensure system security and stability

Troubleshoot complex technical issues

Implement automation to improve efficiency

The beauty of Linux as a career path is that it's accessible to motivated individuals willing to invest time in learning the necessary skills. Unlike some tech specialties that require years of formal education, Linux administration can be mastered through focused training programs and hands-on experience.

The Path to Becoming a Linux System Administrator

1. Structured Learning

The journey begins with structured learning. Comprehensive training programs that cover Linux fundamentals, system administration, networking, and security provide the knowledge base needed to succeed. The most effective programs:

Teach practical, job-relevant skills

Offer instruction from industry professionals

Pace the learning to allow for deep understanding

Prepare students for respected certifications like Red Hat

2. Certification

Industry certifications validate your skills to potential employers. Red Hat certifications are particularly valuable, demonstrating your ability to work with enterprise Linux environments. These credentials help you stand out in a competitive job market and often lead to higher starting salaries.

3. Hands-On Experience

Theoretical knowledge isn't enough—employers want to see practical experience. Apprenticeship opportunities allow aspiring Linux administrators to:

Apply their skills in real-world scenarios

Build a portfolio of completed projects

Gain confidence in their abilities

Bridge the gap between training and employment

4. Job Search Strategy

With the right skills and experience, the final step is finding that first position. Successful job seekers:

Tailor their resumes to highlight relevant skills

Prepare thoroughly for technical interviews

Network with industry professionals

Target companies that value their newly acquired skills

Time Investment and Commitment

Becoming job-ready as a Linux System Administrator typically requires:

10-15+ hours per week for studying

A commitment to consistent learning over several months

Persistence through challenging technical concepts

A growth mindset and motivation to succeed

The Career Outlook

For those willing to make the investment, the rewards can be substantial. Linux professionals enjoy:

Competitive salaries

Strong job security

Opportunities for remote work

Clear paths for career advancement

Intellectually stimulating work environments

Conclusion

The path to becoming a Linux System Administrator is more accessible than many people realize. With the right training, certification, and hands-on experience, motivated individuals can transition into rewarding tech careers—regardless of their previous background. As we continue through 2025, the demand for these skills shows no signs of slowing down, making now an excellent time to begin this journey.

[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.