#AI & ML

[codetradeinsights]

𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗲 𝗬𝗼𝘂𝗿 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗘𝗥𝗣 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀!

Discover how integrating Artificial Intelligence with Enterprise Resource Planning can transform your manufacturing operations. Check out our latest blog post to explore the future of smart manufacturing:

Read more about the next wave of intelligent ERP systems and stay ahead in the digital transformation race!

https://www.codetrade.io/blog/ai-driven-erp-solutions-for-the-manufacturing-industry/

[digitalhub-solution]

Best Website Development, Mobile app Development, Digital Marketing, AI/ML Services.

Digital Hub Solution offers a wide range of services, including web and mobile app development, AI/ML solutions, digital marketing, UI/UX designing, virtual assistant services, and website designing. These services aim to enhance business growth, streamline processes, and improve user experience through innovative and tailored digital solutions.

[innvonixtech]

AI-Driven Recruitment: How Automation is Redefining Talent Acquisition

The evolution of artificial intelligence (AI) is transforming numerous industries, with recruitment being one of the most impacted. Traditional recruitment methods, often characterized by manual processes and human bias, are giving way to AI-driven recruitment strategies that streamline and enhance talent acquisition. By leveraging AI, companies can automate many facets of recruitment, from sourcing candidates to onboarding, ultimately redefining how talent is acquired. This article explores how automation is reshaping recruitment and the benefits it offers to businesses striving to build competitive workforces.

The Rise of AI-Driven Recruitment

AI-driven recruitment involves using artificial intelligence and machine learning (ML) algorithms to automate and optimize various stages of the hiring process. The adoption of AI in recruitment is not merely a trend but a necessity as companies seek to manage large volumes of applications, reduce time-to-hire, and improve the overall candidate experience.

Focus Keyword: AI-Driven Recruitment

At its core, AI-driven recruitment addresses the inefficiencies of traditional hiring methods. Manual screening, which can be time-consuming and prone to errors, is being replaced by AI algorithms that can quickly and accurately assess large volumes of resumes. These algorithms use natural language processing (NLP) and machine learning models to identify key qualifications, skills, and experiences that match job requirements, allowing recruiters to focus on the most promising candidates.

Automation Across the Recruitment Funnel

Automation in recruitment spans multiple stages of the hiring funnel, from sourcing to onboarding. Below are some key areas where AI is making a significant impact:

Candidate Sourcing and Outreach: AI-powered tools can automatically source candidates from various platforms, including job boards, social media, and professional networks like LinkedIn. These tools analyze data to identify potential candidates who match the desired profile. Automation also extends to outreach, where AI-driven chatbots engage with candidates to schedule interviews or provide additional information about the job. By leveraging AI/ML development services, companies can ensure that their sourcing strategies are efficient and data-driven.

Resume ScreeningOne of the most time-consuming aspects of recruitment is resume screening. Traditionally, recruiters manually sift through resumes to identify suitable candidates, which can lead to missed opportunities or biased decisions. AI-driven recruitment tools, powered by machine learning services, can automatically screen resumes, rank candidates based on their qualifications, and even identify patterns that may indicate future performance. This reduces human bias and ensures that the most qualified candidates are not overlooked.

Interview Scheduling and Assessment: Coordinating interviews is another area where AI-driven recruitment shines. AI tools can automate the scheduling process by finding mutually convenient times for both candidates and interviewers. Furthermore, AI-driven assessment tools can analyze interview responses, evaluating them against pre-defined criteria. These assessments can include video interviews where facial expressions, tone of voice, and word choice are analyzed to provide insights into a candidate’s fit for the role.

Onboarding and Employee Experience: The automation of recruitment does not end with hiring. AI-driven onboarding systems can personalize the onboarding experience for new hires, guiding them through training modules, providing relevant resources, and connecting them with mentors. By utilizing Generative AI Services, companies can create tailored onboarding experiences that cater to the individual needs of each new employee, fostering engagement and improving retention rates.

The Benefits of AI-Driven Recruitment

AI-driven recruitment offers several benefits that make it an attractive option for businesses aiming to enhance their talent acquisition strategies. These benefits include:

Improved Efficiency and Speed: By automating repetitive tasks such as resume screening and interview scheduling, AI-driven recruitment drastically reduces the time-to-hire. This allows companies to fill critical roles faster, which is particularly beneficial in competitive job markets where top talent is quickly snapped up.

Enhanced Candidate Experience: Automation ensures that candidates receive timely communication and feedback throughout the hiring process. AI-driven chatbots can answer candidate queries 24/7, providing a seamless experience. Additionally, personalized interactions, made possible by AI/ML development services, make candidates feel valued and respected, improving the overall candidate experience.

Data-Driven Decision Making: AI-driven recruitment provides valuable insights into the hiring process. Data analytics can identify trends, such as the most effective sourcing channels or the characteristics of successful hires. This data-driven approach enables companies to continuously refine their recruitment strategies, ensuring they remain aligned with business goals.

Reduction of Bias: Human bias, whether conscious or unconscious, can negatively impact recruitment decisions. AI-driven recruitment helps mitigate bias by relying on objective data and predefined criteria. Machine learning services can be used to train algorithms to ignore irrelevant factors, such as gender, age, or ethnicity, focusing solely on qualifications and experience.

Challenges and Considerations

While AI-driven recruitment offers numerous advantages, it is not without challenges. One significant concern is the potential for algorithmic bias, where AI models may inadvertently learn and perpetuate biases present in historical data. To mitigate this risk, it is essential for companies to work with experienced AI/ML development services that prioritize fairness and transparency in their models.

Another consideration is the need for human oversight. While AI can automate many tasks, human judgment remains crucial, especially in cultural fit and team dynamics. AI should be viewed as a tool that enhances human capabilities rather than replacing them entirely.

The Future of AI-Driven Recruitment

As AI technology continues to evolve, the role of AI in recruitment will expand. Advanced AI models, powered by Generative AI Services, could potentially simulate real-world job scenarios during the assessment process, providing a more accurate measure of a candidate's abilities. Furthermore, AI could play a role in predicting future talent needs, allowing companies to proactively build talent pipelines.

In conclusion, AI-driven recruitment is transforming talent acquisition by automating time-consuming tasks, improving decision-making, and enhancing the candidate experience. As businesses continue to adopt AI technologies, those that leverage Machine Learning Services will be better positioned to attract, assess, and retain top talent in an increasingly competitive landscape.

[itesservices]

Discover how AI revolutionizes data collection, from chatbots enhancing customer interactions to predictive analytics streamlining operations. Learn the benefits: up to 90% efficiency boost, 99% data accuracy, and 80% cost reduction. Explore smart data transformation services to harness these advantages and propel your business forward. 

[techinsightweekly]

https://www.zymr.com/blog/smart-loans-how-ai-ml-can-help-reimagine-fintech-lending-platforms

The disruption in recent times underscores the dynamic nature of the financial landscape, especially the lending domain. Changing consumer behavior, new emerging technologies like blockchain, and shift in trends in funding and investment have had a severe impact on how fintech lending solutions are accommodated in the mainstream market. Despite rapid growth for a good period, funding for digital lending faces a significant decline of 53%, with just $11.5 billion raised during the year 2022, as per reports. Therefore, there is a need for fintech software development companies to build lending platforms that can regain ground in this ever-changing environment.

A crucial help in this context comes in the form of Artificial Intelligence. The integration of AI/ML will offer the potential for data-driven decision-making and precise lending models. Therefore, in addition to enhanced efficiency and reduced risks AI/ML services will also reignite interest and investor confidence in the digitalized financial services for lending.

In this blog, we will explore, in detail, how AI machine learning can play a pivotal role in building fintech lending platforms to meet the evolving market demands. We'll examine how AI/ML can help bridge the gap between declining funding and a thriving fintech lending ecosystem while maintaining essential features like CRM, LOS, LMS, and more that borrowers and investors rely on.

[apisdor]

Apisdor

At Apisdor, we are driven by a passion for innovation through cutting-edge technology, which is deeply rooted in our DNA.

[anna-scribbles]

adrien tell ur mom to leave me alone !

[nixcraft]

I asked Google "who ruined Google" and they replied honestly using their AI, which is now forced on all of us. It's too funny not to share!

[wildtornado-o]

Doodles :)

I think the Graham de Vanilys should have some cats and ferrets, Félix seems like a ferret liker <3 The doodles on the last image are old ones i never got aroun to posting, mostly consisting of the aged up designs i have 4 feligami

[mostlysignssomeportents]

How plausible sentence generators are changing the bullshit wars

This Friday (September 8) at 10hPT/17hUK, I'm livestreaming "How To Dismantle the Internet" with Intelligence Squared.

On September 12 at 7pm, I'll be at Toronto's Another Story Bookshop with my new book The Internet Con: How to Seize the Means of Computation.

In my latest Locus Magazine column, "Plausible Sentence Generators," I describe how I unwittingly came to use – and even be impressed by – an AI chatbot – and what this means for a specialized, highly salient form of writing, namely, "bullshit":

https://locusmag.com/2023/09/commentary-by-cory-doctorow-plausible-sentence-generators/

Here's what happened: I got stranded at JFK due to heavy weather and an air-traffic control tower fire that locked down every westbound flight on the east coast. The American Airlines agent told me to try going standby the next morning, and advised that if I booked a hotel and saved my taxi receipts, I would get reimbursed when I got home to LA.

But when I got home, the airline's reps told me they would absolutely not reimburse me, that this was their policy, and they didn't care that their representative had promised they'd make me whole. This was so frustrating that I decided to take the airline to small claims court: I'm no lawyer, but I know that a contract takes place when an offer is made and accepted, and so I had a contract, and AA was violating it, and stiffing me for over $400.

The problem was that I didn't know anything about filing a small claim. I've been ripped off by lots of large American businesses, but none had pissed me off enough to sue – until American broke its contract with me.

So I googled it. I found a website that gave step-by-step instructions, starting with sending a "final demand" letter to the airline's business office. They offered to help me write the letter, and so I clicked and I typed and I wrote a pretty stern legal letter.

Now, I'm not a lawyer, but I have worked for a campaigning law-firm for over 20 years, and I've spent the same amount of time writing about the sins of the rich and powerful. I've seen a lot of threats, both those received by our clients and sent to me.

I've been threatened by everyone from Gwyneth Paltrow to Ralph Lauren to the Sacklers. I've been threatened by lawyers representing the billionaire who owned NSOG roup, the notoroious cyber arms-dealer. I even got a series of vicious, baseless threats from lawyers representing LAX's private terminal.

So I know a thing or two about writing a legal threat! I gave it a good effort and then submitted the form, and got a message asking me to wait for a minute or two. A couple minutes later, the form returned a new version of my letter, expanded and augmented. Now, my letter was a little scary – but this version was bowel-looseningly terrifying.

I had unwittingly used a chatbot. The website had fed my letter to a Large Language Model, likely ChatGPT, with a prompt like, "Make this into an aggressive, bullying legal threat." The chatbot obliged.

I don't think much of LLMs. After you get past the initial party trick of getting something like, "instructions for removing a grilled-cheese sandwich from a VCR in the style of the King James Bible," the novelty wears thin:

https://www.emergentmind.com/posts/write-a-biblical-verse-in-the-style-of-the-king-james

Yes, science fiction magazines are inundated with LLM-written short stories, but the problem there isn't merely the overwhelming quantity of machine-generated stories – it's also that they suck. They're bad stories:

https://www.npr.org/2023/02/24/1159286436/ai-chatbot-chatgpt-magazine-clarkesworld-artificial-intelligence

LLMs generate naturalistic prose. This is an impressive technical feat, and the details are genuinely fascinating. This series by Ben Levinstein is a must-read peek under the hood:

https://benlevinstein.substack.com/p/how-to-think-about-large-language

But "naturalistic prose" isn't necessarily good prose. A lot of naturalistic language is awful. In particular, legal documents are fucking terrible. Lawyers affect a stilted, stylized language that is both officious and obfuscated.

The LLM I accidentally used to rewrite my legal threat transmuted my own prose into something that reads like it was written by a $600/hour paralegal working for a $1500/hour partner at a white-show law-firm. As such, it sends a signal: "The person who commissioned this letter is so angry at you that they are willing to spend $600 to get you to cough up the $400 you owe them. Moreover, they are so well-resourced that they can afford to pursue this claim beyond any rational economic basis."

Let's be clear here: these kinds of lawyer letters aren't good writing; they're a highly specific form of bad writing. The point of this letter isn't to parse the text, it's to send a signal. If the letter was well-written, it wouldn't send the right signal. For the letter to work, it has to read like it was written by someone whose prose-sense was irreparably damaged by a legal education.

Here's the thing: the fact that an LLM can manufacture this once-expensive signal for free means that the signal's meaning will shortly change, forever. Once companies realize that this kind of letter can be generated on demand, it will cease to mean, "You are dealing with a furious, vindictive rich person." It will come to mean, "You are dealing with someone who knows how to type 'generate legal threat' into a search box."

Legal threat letters are in a class of language formally called "bullshit":

https://press.princeton.edu/books/hardcover/9780691122946/on-bullshit

LLMs may not be good at generating science fiction short stories, but they're excellent at generating bullshit. For example, a university prof friend of mine admits that they and all their colleagues are now writing grad student recommendation letters by feeding a few bullet points to an LLM, which inflates them with bullshit, adding puffery to swell those bullet points into lengthy paragraphs.

Naturally, the next stage is that profs on the receiving end of these recommendation letters will ask another LLM to summarize them by reducing them to a few bullet points. This is next-level bullshit: a few easily-grasped points are turned into a florid sheet of nonsense, which is then reconverted into a few bullet-points again, though these may only be tangentially related to the original.

What comes next? The reference letter becomes a useless signal. It goes from being a thing that a prof has to really believe in you to produce, whose mere existence is thus significant, to a thing that can be produced with the click of a button, and then it signifies nothing.

We've been through this before. It used to be that sending a letter to your legislative representative meant a lot. Then, automated internet forms produced by activists like me made it far easier to send those letters and lawmakers stopped taking them so seriously. So we created automatic dialers to let you phone your lawmakers, this being another once-powerful signal. Lowering the cost of making the phone call inevitably made the phone call mean less.

Today, we are in a war over signals. The actors and writers who've trudged through the heat-dome up and down the sidewalks in front of the studios in my neighborhood are sending a very powerful signal. The fact that they're fighting to prevent their industry from being enshittified by plausible sentence generators that can produce bullshit on demand makes their fight especially important.

Chatbots are the nuclear weapons of the bullshit wars. Want to generate 2,000 words of nonsense about "the first time I ate an egg," to run overtop of an omelet recipe you're hoping to make the number one Google result? ChatGPT has you covered. Want to generate fake complaints or fake positive reviews? The Stochastic Parrot will produce 'em all day long.

As I wrote for Locus: "None of this prose is good, none of it is really socially useful, but there’s demand for it. Ironically, the more bullshit there is, the more bullshit filters there are, and this requires still more bullshit to overcome it."

Meanwhile, AA still hasn't answered my letter, and to be honest, I'm so sick of bullshit I can't be bothered to sue them anymore. I suppose that's what they were counting on.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/09/07/govern-yourself-accordingly/#robolawyers

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0

https://creativecommons.org/licenses/by/3.0/deed.en

[snarp]

90% of documentation sucks. 99% of LLM documentation sucks. Why? Possibilities:

LLM devs lack the necessary skills to write docs because they're under the age of 25 and have been working on the same couple projects that whole time.

LLM devs don't understand why docs are important because they're under the age of 25 and have been working on the same couple projects that whole time.

LLM devs view their work in the way that mystery cults view their worship, and enter an ecstatic state not conducive to communication upon opening Jupyter Notebook/Google Colab/etc. (It's like when a snake-handling churchgoer picks up the snake.)

LLM devs choose not to write docs because they think that providing publicly-accessible information on how their code can be used makes their expertise less-valuable in the job market:

"If I'm the only one who understands the tools I made, people who want to use my work will have to pay me."

-- Final words of 10,000 naive LLM devs who have spent the last 2 years duplicating each other's work without realizing it, because they have never provided a coherent public explanation of what their work is intended to do, making it impossible either for them to find each other or for prospective users to find them. They died of dysentery.

If they had lived only a few months longer, they'd have gotten back in the computer chair and discovered, with mounting horror, that they no longer know how to use their own work, because they spent a few months doing something else (hospital, PT, etc) and the unwritten knowledge that they thought they had hoarded - in fact recalled only due to near-daily repetition - fell out of their heads, teaching them an important lesson about their own fallibility.

They didn't, though. They died of dysentery. Very sad.

[shoujo-dump]

Museru Kurai no Ai o Ageru

[chocostrwberry]

Felix: I don’t know what you all are talkin about, but it’s probably absolutely ridiculous.

Adrien and Nino:

Nino: AbsoLOOTeLAY

[yeet-noir]

I cannot be trusted with ai Adrien

Bonus:

[anna-scribbles]

i think it would be funny if one of the ways that adrien responded to Everything was by becoming the most offline unreachable hermit of all time. no phone no computer nothing. don’t talk to him about ai or instagram brand deals or twitter drama he can’t even receive a text message. if you want to contact him he checks his email once a week at the local library. he also has a flip phone with customized ringtones and no internet connection, and a number he gives out to an extremely select list of people. don’t try to reference a pop culture phenomenon to him he won’t understand it. his flip phone can’t open tiktoks. he’s protecting his peace.

[nixcraft]