#Automation developing

[technology123]

Technology in hospitality

The drive-through window's introduction in the quick service sector is primarily dependent on communication devices since, in the absence of these, the employee behind the window would not be able to hear the customer's voice. For this reason, communication devices are required in this industry.

2. We use cameras in our restaurant to protect our reputation, the quality of our food and service, the safety of our employees, and the welfare of our customers.

3. The development of technology has allowed for the automation of some HR processes, such as hiring and training, as well as the provision of real-time data and analytics for the optimisation of workforce management.

Hardware developments, especially in robotics, sensors, and IoT devices, will most likely have the largest impact on foodservice operations during the next five years.

[rthidden]

What is an Algorithm in 30 Seconds?

An algorithm is simply a series of instructions.

Think of a recipe: boil water, add pasta, wait, drain, eat. These are steps to follow.

In computer terms, an algorithm is a set of instructions for a computer to execute.

In machine learning, these instructions enable computers to learn from data, making machine learning algorithms unique and powerful.

[kamil-a]

customer service voice vs real voice meme needs to be a thing

[honestlyvan]

Let me be absolutely clear -- the problems with Tumblr will keep getting worse if the disabled minority and the trans people and the people frothing at the mouth at the opportunity to yell at a transphobe, keep @’ing staff and the developers on this site, tell them to kys, because in the meanwhile the transphobes and racists and white supremacists will keep using the actual tools Tumblr provides for blocking and reporting, further poisoning the datasets used for moderation, and encouraging the idea that using the official tools does nothing to basically ensure the only statistically meaningful data available to Automattic is poisoned, poisoned all the way down, poisoned beyond usability.

Hatespeech and bias needs to be reported for it to be considered statstically significant to act on from a developer point of view. Suicide baiting and spamming any of the official means of communication will get you eliminated as a spammer, even if you’re peppering legitimate criticism within your ventpost about how you hate the new thing. You are playing the TE/RFs game.

[ajcgames]

The Big Weekend - Part 1

Part 1 of my 'big weekend' of project development has gone really well so far. Lots of new things added, and progress has been made on my big list of new-things-to-add.

Let's first show everything in a brief video overview:

Whoa! Environments!

I did end up doing some extra work outside of my intended weekend scope, mostly because I wanted a brief distraction from coding. To that end I finally added the first parts of my 'asteroid' environment that your factory is placed in. This will be improved over time, I'm sure, but now serves to make the factory feel a lot more grounded in the very place you're supposed to be!

I also re-added the factory walls, which are now correctly done programmatically - rather than being hand-placed. These scale up with the size of the factory floor, so they're more or less 'done'.

Packager

You can now drop the packager into your factory, which is a necessary first step to exporting your goods from the facility.

Routing items through here will parcel them up ready for transport. You just have to snake them off to your Exporter machine.

Ready for packaging!

Exporter

This machine must be placed over one of the new export nodes. This restricts the number of exporters you can use in any given factory (like the import nodes), and you'll likely have to merge a number of packager belts together to bundle up lots of orders in later stages.

The exporter has space for up to 6 stacks of up to 99 items. A lack of space will result in packages backing up on the import belt, so make sure you don't fill it up with junk!

The build ghost of the exporter next to one of the new Export nodes. These are limited, so you'll have to design your factory around them!

What's next?

Here's my big list of things-to-do, with my completed updates marked off:

Main objectives view

Packager machine

Exporter machine

Research tree

Technology upgrades

Money / credits system

Structure descriptions (QoL)

Audio refinements (QoL)

Main menu screens

New pipes subsytem

Not bad progress so far! I'm not sure what I'm going to tackle tomorrow, though I have a sneaking suspicion I'll want to do the research and tech trees, since they are the next 'big' things to nail down. It will also force me to finally implement a system to prevent access to building items that you haven't yet unlocked, which is a crucial part of progression.

Anyway, that's all I have for this evening. If you reached this point, thank you kindly for your time! And with any luck I'll see you again tomorrow for another progress update.

Have a great evening, wherever you are, and I'll see you again soon! 😊

[codiastic-soft1]

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[fraoula1]

Python for Data Science: From Beginner to Expert – A Complete Guide!

Python has become the go-to language for data science, thanks to its flexibility, powerful libraries, and strong community support. In this video, we’ll explore why Python is the best choice for data scientists and how you can master it—from setting up your environment to advanced machine learning techniques.

🔹 What You'll Learn:

✅ Why Python is essential for data science

✅ Setting up Python and key libraries (NumPy, Pandas, Matplotlib) ✅ Data wrangling, visualization, and transformation

✅ Building machine learning models with Scikit-learn

✅ Best practices to enhance your data science workflow 🚀 Whether you're a beginner or looking to refine your skills, this guide will help you level up in data science with Python. 📌 Don’t forget to like, subscribe, and hit the notification bell for more data science and Python content!

[harrisson-dev]

I need to bring back this big boy to life (image analyser and color palette creator based on k-mean algo)

[techjour]

FIRST PRIORITY IS YOUR HAPPINESS.

Techjour helps C-suite Executives to turn today's challenges into tomorrow’s opportunities. CXOs are busy in building their businesses while We have our set of solutions to offer for them. Team closely work with Clients from to understand requirements to deliver expected results. Among complex set of technologies, we assist Clients to decide number of technologies based on nature of application, their business growth and to reduce cost.

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[jcmarchi]

Eric Schmidt: AI misuse poses an ‘extreme risk’

New Post has been published on https://thedigitalinsider.com/eric-schmidt-ai-misuse-poses-an-extreme-risk/

Eric Schmidt: AI misuse poses an ‘extreme risk’

Eric Schmidt, former CEO of Google, has warned that AI misuse poses an “extreme risk” and could do catastrophic harm.

Speaking to BBC Radio 4’s Today programme, Schmidt cautioned that AI could be weaponised by extremists and “rogue states” such as North Korea, Iran, and Russia to “harm innocent people.”

Schmidt expressed concern that rapid AI advancements could be exploited to create weapons, including biological attacks. Highlighting the dangers, he said: “The real fears that I have are not the ones that most people talk about AI, I talk about extreme risk.”

Using a chilling analogy, Schmidt referenced the al-Qaeda leader responsible for the 9/11 attacks: “I’m always worried about the Osama bin Laden scenario, where you have some truly evil person who takes over some aspect of our modern life and uses it to harm innocent people.”

He emphasised the pace of AI development and its potential to be co-opted by nations or groups with malevolent intent.

“Think about North Korea, or Iran, or even Russia, who have some evil goal … they could misuse it and do real harm,” Schmidt warns.

Oversight without stifling innovation

Schmidt urged governments to closely monitor private tech companies pioneering AI research. While noting that tech leaders are generally aware of AI’s societal implications, they may make decisions based on different values from those of public officials.

“My experience with the tech leaders is that they do have an understanding of the impact they’re having, but they might make a different values judgement than the government would make.”

Schmidt also endorsed the export controls introduced under former US President Joe Biden last year to restrict the sale of advanced microchips. The measure is aimed at slowing the progress of geopolitical adversaries in AI research.  

Global divisions around preventing AI misuse

The tech veteran was in Paris when he made his remarks, attending the AI Action Summit, a two-day event that wrapped up on Tuesday.

The summit, attended by 57 countries, saw the announcement of an agreement on “inclusive” AI development. Signatories included major players like China, India, the EU, and the African Union.  

However, the UK and the US declined to sign the communique. The UK government said the agreement lacked “practical clarity” and failed to address critical “harder questions” surrounding national security. 

Schmidt cautioned against excessive regulation that might hinder progress in this transformative field. This was echoed by US Vice-President JD Vance who warned that heavy-handed regulation “would kill a transformative industry just as it’s taking off”.  

This reluctance to endorse sweeping international accords reflects diverging approaches to AI governance. The EU has championed a more restrictive framework for AI, prioritising consumer protections, while countries like the US and UK are opting for more agile and innovation-driven strategies. 

Schmidt pointed to the consequences of Europe’s tight regulatory stance, predicting that the region would miss out on pioneering roles in AI.

“The AI revolution, which is the most important revolution in my opinion since electricity, is not going to be invented in Europe,” he remarked.

Prioritising national and global safety

Schmidt’s comments come against a backdrop of increasing scrutiny over AI’s dual-use potential—its ability to be used for both beneficial and harmful purposes.

From deepfakes to autonomous weapons, AI poses a bevy of risks if left without measures to guard against misuse. Leaders and experts, including Schmidt, are advocating for a balanced approach that fosters innovation while addressing these dangers head-on.

While international cooperation remains a complex and contentious issue, the overarching consensus is clear: without safeguards, AI’s evolution could have unintended – and potentially catastrophic – consequences.

(Photo by Guillaume Paumier under CC BY 3.0 license. Cropped to landscape from original version.)

See also: NEPC: AI sprint risks environmental catastrophe

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[rthidden]

The Frame Problem: AI's Unseen Nemesis

The frame problem is AI's Achilles' heel, lurking since the 1960s and still unresolved.

1. The Robot Dilemma

Daniel Dennett's thought experiment illustrates the issue: a robot must save its battery from a room with a bomb.

Initially, the robot pulls the battery on a cart but also drags the bomb out, unaware of this side effect.

Solution attempts include programming awareness of side effects, leading to analysis paralysis as the robot debates endless possibilities.

2. The Side Effect Spiral

When programmed to consider all side effects, the robot wastes time on irrelevant details—like pondering wall color changes.

This shows how difficult it is for AI to filter relevant from irrelevant information without getting bogged down.

3. Human Intuition vs. AI Logic

Humans effortlessly ignore irrelevant details, making quick decisions in complex contexts.

Programming AI to mimic this selective ignorance is resource-intensive and remains a significant challenge.

The frame problem underscores a subtle yet crucial aspect of human intelligence: our ability to instantly prioritize relevant information. As we advance in AI development, solving this problem will be key to creating truly intelligent systems.

Got thoughts on tackling the frame problem? Share your ideas!

[precisiotech]

Automated Testing vs. Manual Testing: Which One is Right for Your Project?

Achieving high-quality, reliable software stands as a fundamental requirement in software development. Successful testing functions as an essential tool to discover faults and build performance capabilities that create better user experience outcomes. Two main testing methods dominate the field: automated testing and manual testing. The process of quality software assurance uses different testing approaches that demonstrate their own advantages as well as weaknesses according to specific project requirements and scenarios. We will explore the specifics to determine which testing process works best for your system development efforts.

1. What Is Manual Testing?

Manual testing involves a human tester manually executing test cases without using automation tools. Key Characteristics:

The methodology focuses its efforts on user interface together with usability and experience testing.

Human-centered applications where selection requires discretion include ad hoc testing and enumerative testing as well as examinations that need human evaluation.

Human performers are required during this approach; thus, it demands substantial time.

2. What Is Automated Testing?

Software performing automated testing executes test cases through workflows and helpers. Key Characteristics:

Efficient for repetitive and regression testing.

Users must spend money on tools along with developing custom scripts for testing.

Reduces human error.

3. Advantages of Manual Testing

Human Intuition: Software testing professionals can detect kernels through their human cognitive ability that automated tools cannot match. The observation and evaluation of visual elements runs more efficiently through human operatives instead of advanced tools.

Flexibility: This method suits exploratory testing specifically because there are no pre-determined scripts available.

Low Initial Investment: Running this approach does not need tool purchases or applications to develop automation frameworks.

Adaptable for UI/UX Testing: Running this approach does not need tool purchases or applications to develop automation frameworks.

4. Advantages of Automated Testing

Speed: Executes repetitive tests much faster than humans.

Scalability: The system proves most effective for extensive projects that need constant system updates.

Accuracy: When performing recurring actions, automated systems minimize the chances of human mistakes.

Cost-Efficient in the Long Run: Once established and implemented, the system demands costly investments but ensures continuous development expenses decrease over time.

Better for CI/CD Pipelines: Such testing technology connects various development pipelines that support agile and DevOps methodologies.

5. Disadvantages of Manual Testing

Time-Consuming: The manual performance of repeated tests leads to delayed completion of projects.

Error-Prone: Large applications contain tiny bugs that human testers commonly fail to detect.

Not Ideal for Scalability: The process of increasing manual testing needs additional testers to avoid cost escalations.

6. Disadvantages of Automated Testing

Initial Costs: Organizations must provide high financial resources to procure testing tools together with developing programming constructs.

Limited to Pre-Defined Scenarios: These testing approaches work poorly for handling exploratory or ad hoc testing.

Requires Maintenance: Test scripts need frequent updates when application changes occur.

Not Suitable for UI/UX Testing: Struggles with subjective user experience evaluations.

7. When to Use Manual Testing

Small Projects: The testing method proves beneficial at a low cost for small applications and provides quick assessments.

Exploratory Testing: Testing this approach benefits projects whose scripts have not been defined yet or need evaluation for newly added features.

Visual and Usability Testing: Performing assessments on interface components together with design features.

8. When to Use Automated Testing

Large Projects: Handles scalability for projects with frequent updates.

Regression Testing: Program testing becomes more efficient through automation since automated assessments perform multiple tests following each update process.

Performance Testing: The system performs efficient capabilities to conduct load testing and stress testing.

Continuous Development Environments: Agile progression and DevOps implementations need automation as a core requirement.

READ MORE- https://www.precisio.tech/automated-testing-vs-manual-testing-which-one-is-right-for-your-project/

[arundolyn]

man my tolerance for annoying people is just . Nonexistent huh

[manojbiswas]

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[jakeperalta]

the hustle is paying off 🤑👊💯💰💸