#agile model

[raffaellopalandri]

Statistical Tools

Daily writing promptWhat was the last thing you searched for online? Why were you looking for it?View all responses Checking which has been my most recent search on Google, I found that I asked for papers, published in the last 5 years, that used a Montecarlo method to check the reliability of a mathematical method to calculate a team’s efficacy. Photo by Andrea Piacquadio on Pexels.com I was…

[fellhellion]

Saying this w love but Atsv Miguel isn’t even that good of a fighter, he’s just got a health bar the size of an Elden Ring boss

[stardustdiver]

the br kids have forgotten their stw roots 😔

TBH that might even thiner they avrage

[sassypizzapatrol]

Kaela the Shadowblade Enchantress Lowpoly 3D Model

3D Model Specifications

8,036 Polygons

6,067 Vertices

Polygonal Tris only Geometry

[hallofflame]

3D Raptorox The Swiftclaw Lowpoly Model

3D Model Specifications

7,946 Polygons

6,010 Vertices

Polygon Geometry

[raffaellopalandri]

My life in three years from now?

Daily writing promptWhat will your life be like in three years?View all responses In three years, my life will be both a continuation of my current path and a testament to the accumulated wisdom of that journey. Photo by Ricky Esquivel on Pexels.com Even though I don’t create elaborate plans for a future date as distant as three years, I trust that my principles and the habits I cultivate…

[business901-blog]

Implicit guidance and control (IGC) is a crucial component of the OODA loop process that often goes unnoticed. It refers to the subconscious processing and intuitive decision-making based on past experiences, cultural norms, and internalized knowledge. This hidden driver shapes individuals’ observations, orientation, decisions, and actions in complex environments. 

The IGC process allows the brain to process vast amounts of information without conscious awareness, enabling rapid and effective decision-making. It draws upon previous experience and subconscious processing to guide real-time actions, especially in high-pressure situations. This aspect of the OODA loop is particularly important for experienced professionals, as it allows them to make quick and informed decisions based on their intuition and past experiences.

[cyber-soul-smartz]

21st Century Project Planning: Blueprint for Unparalleled Success

Discover the secrets to mastering project planning and achieving unparalleled success! Dive into our latest article for expert insights and practical tips. Don't miss out—subscribe now to stay updated on the best strategies for professional development!

Mastering Project Planning: Crafting the Blueprint for Unparalleled Success in the 21st Century Imagine venturing on a journey without a map, a compass, or even a clear destination in mind. The chance of reaching your goal would be slim to none. This scenario mirrors the challenges faced by project managers who dive into execution without a solid plan in place. The planning phase of project…

[rtrevisan]

BIM e o processo de projeto [GA]

Estamos em um momento histórico de transição para um ecossistema de desenvolvimento de projetos mais colaborativo e interconectado. As ferramentas, processos e formas de trabalhar estão mudando rapidamente para uma realidade de projeto simultâneo e de interoperabilidade em tempo real. E os desafios se apresentam com a mesma rapidez em diversos aspectos. Um dos mais importantes certamente é a…

[sassypizzapatrol]

Nyla the Desert Dancer Lowpoly 3D Model

3D Model Specifications

8,604 Polygons

6,174 Vertices

Polygonal Tris only Geometry

[techygrowth]

Agile Software is a Software Development Methodologies. That provides team collaboration, flexibility, and customer satisfaction. Agile Software Development delivery product quickly & frequently. It involves collaboration between the development team and the customer to ensure that product meets the customer.

[melangedeparfums]

KEEP YOUR HANDS ON ME

husband!nanami x wife!reader

masterlist

tw: suggestive, not proofread, nanami can’t keep his hands off, petnames (“my love”, “my wife”)

nanami was good with his hands.

calloused hands trained by years of practice, manipulating weapons, combining agility and strength. his hands could destroy, wreck, bring everything to ruin - but for you, they create, soften, take care.

the roughness of his hands would meet the softness of your skin, the relief of his fingers on your thin skin - making him hum appreciatively, the slowness of his movements overwhelming you.

his hands were also large, much larger than yours, twice your size in fact, wrapping around every part of your flesh with utter care and patience because, yes, nanami was a man of patience, and he intended to make every bit last.

“see how my hands are made for you? see how you fit perfectly, hmm?” his deep voice made his chest grumble, arising goosebumps on your skin, his sharp look reflecting his focused mind.

nanami learnt to be delicate with his fists, his knuckles grazing over the swell of your breasts, his pants already tight. but Nanami was a man of control, and calm, and he would take his sweet time with you.

nanami knew what to do with his hands. always. when to came to you, it was natural. instinctive. his powerful hands could manhandle you, pin you down, and make you bend for him - his eyes captivated by the magnificent arch of your back against the mattress.

precise.

this man was a man of precision. aiming perfectly at his target. one look, and he didn’t have to think - his fingers moving for him, as he would take sight of you, spread for him. he knew where to touch, caress, pinch. alternating between his index and his thumb. gripping with both hands. slapping. the cold metal of his wedding ring shining through the light, trailing along your spine with finesse, his lips following the same path he created before.

“you are truly breathtaking, my love.”

my love.

you thought your heart would explode, your head dizzy and your vision blurred. something utterly tender in his honeyed tone made your core ache with pain, as his hands memorised the map of your body in the marble of his mind, his fingers foxtrotted on your epidermis gracefully to brand every scar, mole, stretch mark, freckle, birthmark into the furrows of his soul.

like a sculptor modelling the clay with an utter precision, kneading the dough between his fingers, awe shining in his hazel irises in front of the muse that made his heart pound deliciously into his ribcage.

veiny forearms that wrapped around your waist, making you switch positions, his digits pressing into the plumpness of your thighs to make it collide with his pelvis, eliciting a weak whimper from you, and a soft chuckle from him.

an work of art, you were his work of art. and Nanami was the artist, holding moonlight in his two hands all night long.

“my wife.”

──── ୨୧ ────

thank you so much for all the likes and the reposts!! 🫶🏻

[reasonsforhope]

It’s an open secret in fashion. Unsold inventory goes to the incinerator; excess handbags are slashed so they can’t be resold; perfectly usable products are sent to the landfill to avoid discounts and flash sales. The European Union wants to put an end to these unsustainable practices. On Monday, [December 4, 2023], it banned the destruction of unsold textiles and footwear.

“It is time to end the model of ‘take, make, dispose’ that is so harmful to our planet, our health and our economy,” MEP Alessandra Moretti said in a statement. “Banning the destruction of unsold textiles and footwear will contribute to a shift in the way fast fashion manufacturers produce their goods.”

This comes as part of a broader push to tighten sustainable fashion legislation, with new policies around ecodesign, greenwashing and textile waste phasing in over the next few years. The ban on destroying unsold goods will be among the longer lead times: large businesses have two years to comply, and SMEs have been granted up to six years. It’s not yet clear on whether the ban applies to companies headquartered in the EU, or any that operate there, as well as how this ban might impact regions outside of Europe.

For many, this is a welcome decision that indirectly tackles the controversial topics of overproduction and degrowth. Policymakers may not be directly telling brands to produce less, or placing limits on how many units they can make each year, but they are penalising those overproducing, which is a step in the right direction, says Eco-Age sustainability consultant Philippa Grogan. “This has been a dirty secret of the fashion industry for so long. The ban won’t end overproduction on its own, but hopefully it will compel brands to be better organised, more responsible and less greedy.”

Clarifications to come

There are some kinks to iron out, says Scott Lipinski, CEO of Fashion Council Germany and the European Fashion Alliance (EFA). The EFA is calling on the EU to clarify what it means by both “unsold goods” and “destruction”. Unsold goods, to the EFA, mean they are fit for consumption or sale (excluding counterfeits, samples or prototypes)...

The question of what happens to these unsold goods if they are not destroyed is yet to be answered. “Will they be shipped around the world? Will they be reused as deadstock or shredded and downcycled? Will outlet stores have an abundance of stock to sell?” asks Grogan.

Large companies will also have to disclose how many unsold consumer products they discard each year and why, a rule the EU is hoping will curb overproduction and destruction...

Could this shift supply chains?

For Dio Kurazawa, founder of sustainable fashion consultancy The Bear Scouts, this is an opportunity for brands to increase supply chain agility and wean themselves off the wholesale model so many rely on. “This is the time to get behind innovations like pre-order and on-demand manufacturing,” he says. “It’s a chance for brands to play with AI to understand the future of forecasting. Technology can help brands be more intentional with what they make, so they have less unsold goods in the first place.”

Grogan is equally optimistic about what this could mean for sustainable fashion in general. “It’s great to see that this is more ambitious than the EU’s original proposal and that it specifically calls out textiles. It demonstrates a willingness from policymakers to create a more robust system,” she says. “Banning the destruction of unsold goods might make brands rethink their production models and possibly better forecast their collections.”

One of the outstanding questions is over enforcement. Time and again, brands have used the lack of supply chain transparency in fashion as an excuse for bad behaviour. Part of the challenge with the EU’s new ban will be proving that brands are destroying unsold goods, not to mention how they’re doing it and to what extent, says Kurazawa. “Someone obviously knows what is happening and where, but will the EU?”"

-via British Vogue, December 7, 2023

[jcmarchi]

Nick Kathmann, CISO/CIO at LogicGate – Interview Series

New Post has been published on https://thedigitalinsider.com/nick-kathmann-ciso-cio-at-logicgate-interview-series/

Nick Kathmann, CISO/CIO at LogicGate – Interview Series

Nicholas Kathmann is the Chief Information Security Officer (CISO) at LogicGate, where he leads the company’s information security program, oversees platform security innovations, and engages with customers on managing cybersecurity risk. With over two decades of experience in IT and 18+ years in cybersecurity, Kathmann has built and led security operations across small businesses and Fortune 100 enterprises.

LogicGate is a risk and compliance platform that helps organizations automate and scale their governance, risk, and compliance (GRC) programs. Through its flagship product, Risk Cloud®, LogicGate enables teams to identify, assess, and manage risk across the enterprise with customizable workflows, real-time insights, and integrations. The platform supports a wide range of use cases, including third-party risk, cybersecurity compliance, and internal audit management, helping companies build more agile and resilient risk strategies

You serve as both CISO and CIO at LogicGate — how do you see AI transforming the responsibilities of these roles in the next 2–3 years?

AI is already transforming both of these roles, but in the next 2-3 years, I think we’ll see a major rise in Agentic AI that has the power to reimagine how we deal with business processes on a day-to-day basis. Anything that would usually go to an IT help desk — like resetting passwords, installing applications, and more — can be handled by an AI agent. Another critical use case will be leveraging AI agents to handle tedious audit assessments, allowing CISOs and CIOs to prioritize more strategic requests.

With federal cyber layoffs and deregulation trends, how should enterprises approach AI deployment while maintaining a strong security posture?

While we’re seeing a deregulation trend in the U.S., regulations are actually strengthening in the EU. So, if you’re a multinational enterprise, anticipate having to comply with global regulatory requirements around responsible use of AI. For companies only operating in the U.S., I see there being a learning period in terms of AI adoption. I think it’s important for those enterprises to form strong AI governance policies and maintain some human oversight in the deployment process, making sure nothing is going rogue.

What are the biggest blind spots you see today when it comes to integrating AI into existing cybersecurity frameworks?

While there are a couple of areas I can think of, the most impactful blind spot would be where your data is located and where it’s traversing. The introduction of AI is only going to make oversight in that area more of a challenge. Vendors are enabling AI features in their products, but that data doesn’t always go directly to the AI model/vendor. That renders traditional security tools like DLP and web monitoring effectively blind.

You’ve said most AI governance strategies are “paper tigers.” What are the core ingredients of a governance framework that actually works?

When I say “paper tigers,” I’m referring specifically to governance strategies where only a small team knows the processes and standards, and they are not enforced or even understood throughout the organization. AI is very pervasive, meaning it impacts every group and every team. “One size fits all” strategies aren’t going to work. A finance team implementing AI features into its ERP is different from a product team implementing an AI feature in a specific product, and the list continues. The core ingredients of a strong governance framework vary, but IAPP, OWASP, NIST, and other advisory bodies have pretty good frameworks for determining what to evaluate. The hardest part is figuring out when the requirements apply to each use case.

How can companies avoid AI model drift and ensure responsible use over time without over-engineering their policies?

Drift and degradation is just part of using technology, but AI can significantly accelerate the process. But if the drift becomes too great, corrective measures will be needed. A comprehensive testing strategy that looks for and measures accuracy, bias, and other red flags is necessary over time. If companies want to avoid bias and drift, they need to start by ensuring they have the tools in place to identify and measure it.

What role should changelogs, limited policy updates, and real-time feedback loops play in maintaining agile AI governance?

While they play a role right now to reduce risk and liability to the provider, real-time feedback loops hamper the ability of customers and users to perform AI governance, especially if changes in communication mechanisms happen too frequently.

What concerns do you have around AI bias and discrimination in underwriting or credit scoring, particularly with “Buy Now, Pay Later” (BNPL) services?

Last year, I spoke to an AI/ML researcher at a large, multinational bank who had been experimenting with AI/LLMs across their risk models. The models, even when trained on large and accurate data sets, would make really surprising, unsupported decisions to either approve or deny underwriting. For example, if the words “great credit” were mentioned in a chat transcript or communications with customers, the models would, by default, deny the loan — regardless of whether the customer said it or the bank employee said it. If AI is going to be relied upon, banks need better oversight and accountability, and those “surprises” need to be minimized.

What’s your take on how we should audit or assess algorithms that make high-stakes decisions — and who should be held accountable?

This goes back to the comprehensive testing model, where it’s necessary to continuously test and benchmark the algorithm/models in as close to real time as possible. This can be difficult, as the model output may have desirable results that will need humans to identify outliers. As a banking example, a model that denies all loans flat out will have a great risk rating, since zero loans it underwrites will ever default. In that case, the organization that implements the model/algorithm should be responsible for the outcome of the model, just like they would be if humans were making the decision.

With more enterprises requiring cyber insurance, how are AI tools reshaping both the risk landscape and insurance underwriting itself?

AI tools are great at disseminating large amounts of data and finding patterns or trends. On the customer side, these tools will be instrumental in understanding the organization’s actual risk and managing that risk. On the underwriter’s side, those tools will be helpful in finding inconsistencies and organizations that are becoming immature over time.

How can companies leverage AI to proactively reduce cyber risk and negotiate better terms in today’s insurance market?

Today, the best way to leverage AI for reducing risk and negotiating better insurance terms is to filter out noise and distractions, helping you focus on the most important risks. If you reduce those risks in a comprehensive way, your cyber insurance rates should go down. It’s too easy to get overwhelmed with the sheer volume of risks. Don’t get bogged down trying to address every single issue when focusing on the most critical ones can have a much larger impact.

What are a few tactical steps you recommend for companies that want to implement AI responsibly — but don’t know where to start?

First, you need to understand what your use cases are and document the desired outcomes. Everyone wants to implement AI, but it’s important to think of your goals first and work backwards from there — something I think a lot of organizations struggle with today. Once you have a good understanding of your use cases, you can research the different AI frameworks and understand which of the applicable controls matter to your use cases and implementation. Strong AI governance is also business critical, for risk mitigation and efficiency since automation is only as useful as its data input. Organizations leveraging AI must do so responsibly, as partners and prospects are asking tough questions around AI sprawl and usage. Not knowing the answer can mean missing out on business deals, directly impacting the bottom line.

If you had to predict the biggest AI-related security risk five years from now, what would it be — and how can we prepare today?

My prediction is that as Agentic AI is built into more business processes and applications, attackers will engage in fraud and misuse to manipulate those agents into delivering malicious outcomes. We have already seen this with the manipulation of customer service agents, resulting in unauthorized deals and refunds. Threat actors used language tricks to bypass policies and interfere with the agent’s decision-making.

Thank you for the great interview, readers who wish to learn more should visit LogicGate. 

[sabelacarsonsblog]

What is Waterfall Model in Software Development

Explore the core principles of the Waterfall Model in software development, delving into its step-by-step methodology, various phases, and its significance in the development of enterprise applications.