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[Table] Artificial intelligence is taking over our lives. We’re the MIT Technology Review team who created a podcast about it, “In Machines We Trust.” Ask us anything!

The AMA began with:
Hi! This is Benji Rosen, MIT Technology Review's social media editor. Jennifer, Tate, Will, and Karen will be responding to your questions periodically throughout the day. They'd also love to know if you've heard the podcast and if you have any favorite episodes or moments. and ended with: Thank you all for your incredibly thoughtful questions. We really enjoyed this. We're going to call it, but we'll be checking our inbox if you have any new questions about the podcast, artificial intelligence, and its future. We also hope you'll listen to In Machines We Trust. Thank you again! This was fun!
Questions Answers
AI good or AI bad? Neither! That's not to say AI is neutral, no technology is. But technology has the assumptions, biases, opinions, hopes and motivations of the people who make it baked in. So some AI is good, some bad. Some good AI is used in bad ways, some bad AI is used in good ways. And that's why we should always question it. [Will Douglas Heaven]
Hi! My name’s Michael Brent. I work in Tech Ethics & Responsible Innovation, most recently as the Data Ethics Officer at a start-up in NYC. I’m thrilled to learn about your podcast and grateful to you all for being here. My question is slightly selfish, as it relates to my own work, but I wonder about your thoughts on the following: How should companies that build and deploy machine learning systems and automated decision-making technologies ensure that they are doing so in ways that are ethical, i.e., that minimize harms and maximize the benefits to individuals and societies? Cheers! Hi Michael! Wow, jumping in with the easy questions there .. I'll start with an unhelpful answer and say that I don't think anyone really knows yet. How to build ethical AI is a matter of intense debate, but (happily) a burgeoning research field. I think some things are going to be key, however: ethics cannot be an afterthought, it needs to be part of the engineering process from the outset. Jess Whittlestone at the University of Cambridge talks about this well: https://www.technologyreview.com/2020/06/24/1004432/ai-help-crisis-new-kind-ethics-machine-learning-pandemic/. Assumptions need to be tested, designs explored, potential side-effects brainstormed well before the software is deployed. And that also means thinking twice about deploying off-the-shelf AI in new situations. For example, many of the problems with facial recognition systems or predictive policing tech is that it is trained on one set of individuals (white, male) but used on others, e.g. https://www.technologyreview.com/2020/07/17/1005396/predictive-policing-algorithms-racist-dismantled-machine-learning-bias-criminal-justice/. It also means realising that AI that works well in a lab rarely works as well in the wild, whether we're talking about speech recognition (which fails on certain accents) or medical diagnosis (which fails in the chaos of a real-world clinic). But people are slowly realising this. I thought this Google team did a nice study, for example: https://www.technologyreview.com/2020/04/27/1000658/google-medical-ai-accurate-lab-real-life-clinic-covid-diabetes-retina-disease/. Another essential, I'd say, is getting more diverse people involved in making these systems: different backgrounds, different experiences. Everyone brings bias to what they do. Better to have a mix of people with a mix of biases. [Will Douglas Heaven]
My son is interested in a career in Robotics combined with A.I. What advice do you have for a future innovator to prepare for a career in the field? He’s 13 years old Yes, curiosity and encouragement! And if you're after core skills, here's what one of DeepMind's founders told a 17 yo who asked the same question a couple of years ago: https://twitter.com/ShaneLegg/status/1024289820665950208. These are always going to be slightly subjective, though. Tinkering with code is probably most useful and there are loads of freely available bits of code and even ML models available online. But do encourage him to keep broad interests and skills: many of AI's current problems stem from the fact that today's innovators have homogenous world-views and backgrounds. [Will Douglas Heaven]
Never lose your curiosity. Better yet, make time to feed and encourage it as innovation is as much about imagination and inquisitiveness as anything else.
What is the most surprising thing you found in your research? Hi! I'm Tate Ryan-Mosley, one of the IMWT producers. This is actually an amazing question because so many things have surprised me but also none of those things maybe should have been surprising? (Perhaps this says more about me?) But I think that the challenge of how we actually integrate AI into social/political structures and our more intimate lives is just so much more complicated and urgent and prevalent than I thought. We've talked to incredibly smart people, most of whom really are doing their best to make the world a better place. And yet it sometimes feels like AI is making the world a worse place, or at the very least, being implemented so quickly that its impact is precarious. I also think I've been surprised by secrecy in the industry. So many of these implementations happen without real public consent or awareness.
☝️ - Jennifer
Been listening to the podcast so far and I'm enjoying it. Thank you for creating it! With algorithms being closed source/IP or AI being almost unfathomably complex after significant training on data sets. What can be done to educate the general population on the security/ethics and design of such systems? People can be very sceptical with regards to things they don't understand. Side question: I really like the book Hello World by Hannah Fry on a similar subject, what media/podcasts/books would you recommend to somebody interested in AI tech as a hobby if you will but without experience in how these systems work. This is an awesome question and thanks so much for listening! One of our main goals with the podcast is to ensure "our moms can understand" everything we publish. We have very smart moms :) but the point is that the general public often gets left in the dark when it comes to how a lot of AI works and even when it is employed. Its a big motivating factor for a lot of our journalism at Tech Review! Not to make this sound like a plug but I think a good way to help educate the public on technology is to subscribe to outlets doing good journalism in the space. (You can subscribe to TR here) Law makers, educators, companies and researchers all play a role in the solution space in my personal opinion.
Side answer- there are a lot of good Ted Talks, Karen Hao's newsletter The Algorithm, I like Kevin Kelly's books. For podcasts: Jennifer Strong's alma matter The Future of Everything from WSJ, Recode is also great! - Tate Ryan-Mosley
Thanks for listening! Have you also tried listening to "Consequential" from Carnegie Mellon or "Sleepwalkers" from iHeart? - Jennifer
the below is a reply to the above
Really appreciate the reply. Is there anyway of getting a small trial for the site? Interested but $50 isn't change for a site I can't experience. Thanks again and look forward to more podcast episodes! Including the 2 you mentioned! You can read a lot of our content for free now at technologyreview.com. FYI, you will be limited to 3 articles per month for a lot of the content, but it'll give you a taste for a lot of the stuff we write about. Send us an email at [[email protected]](mailto:[email protected]), and we can talk through other ways you can get access to our content. Thanks again for your support as a listener and as a reader! - Benji
What do you think is the role of private players / government regulations in trying to promote a sustainable/good use of AI? How will you envision such regulations to look like (and how might we achieve them)? Hello! This is Karen, senior AI reporter at Tech Review. This is an excellent question. I think private players have the unique advantage of innovating quickly and taking risks to achieve greater benefits from AI, whereas government regulators have the important role of setting down guardrails to prevent the harms of AI. So we need both! There's a push and pull. As for what regulations should look like, here's a really awesome Q&A I did with Amba Kak, the director of global strategy and programs at the New York–based AI Now Institute: https://www.technologyreview.com/2020/09/04/1008164/ai-biometric-face-recognition-regulation-amba-kak/. She answers the question much better than I could for face recognition specifically. It offers a great use case into how to think about regulating different AI systems.
What jobs are we most likely to lose to AI in the next 10 years? u/CapnBeardbeard, we recently found that the pandemic might actually accelerate job losses for some essential workers. That would be the people who deliver goods, work at store checkouts, drive buses and trains, and process meat at packing plants. What we don't know is if these job losses to robots will lead to new jobs to help them. This story we published in June provides an extensive overview of what we're talking about. - Benji
It's hard to say exactly how automation will change the job market. Many jobs will change, but not necessarily disappear. AI will also make some aspects of remote working easier, which will also have a big impact. One manager who can keep an eye on a construction site or a warehouse remotely, using smart surveillance tech, will be able to do the job of multiple managers who need to be on site. Some types of job will be safe for some time yet: anything that requires a personal touch, from service industry roles in restaurants and hotels to teachers (tho see that point about remote working again) to sales-people to creatives (but here we should expect a lot of AI tools to make some aspects of creative jobs quite different). [Will Douglas Heaven]
Oh and don't write off cabbies anytime soon: we're still a long way from driverless cars that can navigate rush hour in NYC ;) [Will Douglas Heaven]
With the number of improvements in AI especially over the last 5 to 10 years, do you believe that the Singularity has moved up? Nope. I think the advances in AI in the last decade have been staggering. We've seen AI do things even insiders didn't expect, from beating human champions at Go to highly accurate image recognition to astonishingly good language mimics like GPT-3. But none of these examples have anything like intelligence or an understanding of the world. If you take the singularity to mean the point at which AI becomes smart enough to make itself smarter, leading to an exponential intelligence explosion, then I don't think we are any closer than we've ever been. For me, personally, the singularity is science fiction. There are people who would strongly disagree but then this kind of speculation is a matter of faith! [Will Douglas Heaven]
We actually have a big piece on AGI coming out next week: what it means to different people and why it matters. But in the meantime, you might be interested in a quick round-up of some first impressions of GPT-3 that I put together a couple of months back https://www.technologyreview.com/2020/07/20/1005454/openai-machine-learning-language-generator-gpt-3-nlp/ [Will Douglas Heaven]
Back in Highschool I did a bunch of papers analyzing some of the work one of your professors did. I think it Eric Brybjolfson. He brought up how as technology advances new jobs are created. Do you think we will see things like that with the advancement of AI? Absolutely. Jobs will change, but not always go away. And new jobs will be created. With advances in AI, there will be new tech industries in data science and modelling. But that's just to take a narrow view. AI will impact every aspect of our lives and we want humans working in roles alongside it, whatever the industry. I think we're going to see a lot of collaborative roles where people and AIs work together. [Will Douglas Heaven]
Will people one day have their own AI in some sense? I think that's likely, yes. Personalization is a big attraction. In a way that's what virtual assistants like Siri are already trying to be and the AI in "Her" just takes that idea and runs with it. We could also have different personal AIs for different parts of our life, like an entertainment one at home or a work one that we collaborated with professionally. [Will Douglas Heaven]
That's a really interesting question. For the sake of making a science-fiction analogy, you mean like in the movie, "Her"? Do you mean a personal assistant with a personality?
Perhaps something like this? https://podcasts.apple.com/us/podcast/whats-behind-a-smile/id1523584878?i=1000492216110
Will AI pose a risk in personal data security as more devices are connected? I was reading that smart cities will be able to be hacked posing a lot of risk in our energy systems. The airport in Ukraine has already been hacked and there have been blackouts induced because of this connectivity. Could AI hack also other systems or can it help and “patch” those holes in open and unprotected networks? Yes, this is a big concern. As more devices come online, there will be more opportunities to hack them—both with AI and non-AI techniques. You are right that in some cases AI can help catch these hacks faster, by detecting anomalies in the way devices are operating and data is being exchanged.
In other ways, AI causes the vulnerability. For example, AI-powered digital devices a unique vulnerability to something known as adversarial attacks. This is when someone spoofs an AI system into making an error by feeding it corrupted data. In research, this has been shown to make a self-driving car speed past a stop sign, a Tesla switch into the oncoming traffic lane, and medical AI systems give the wrong diagnosis, among many other worrying behaviors. Some experts are also gravely concerned about what these hacks could mean for semi-autonomous weapons.
Currently, the best research tells us we can fight adversarial attacks by giving our AI systems more "common sense" and a greater understanding of cause and effect (as opposed to mere correlation). But how to do that is still a very active research area, and we're awaiting solutions. —Karen Hao
100% agree with Karen. This is a couple years old but unpacks some existing smart city complexity. -Jennifer
the below is a reply to the above
Karen or Jennifer do you think that by making AI open source could help making “common sense” or would that make it worse? A lot of AI is already open source! But yes, to slightly shift your question, I think getting more people involved in AI development is always a good thing. The more people there are, the more ideas there are; the more ideas, the more innovation; and hopefully the more innovation, the more quickly we reach common sense machines! —Karen Hao
the below has been split into two
1. Would you trust in "AI" made by corporation you have no influence over ? why/why not ? Great questions. Nope! And that's because companies build their AI systems heavily incentivized by their own financial interests rather than by what is best for the user. It's part of the reason why I think government regulation of AI systems in democratic countries is so important for accountability.
2. What will you do if such an "AI" would be used to decide anything about your life without your insight or permission ? Well, this is kind of already happening. Not one single AI but many. I rely heavily on products from all the tech giants, which each have their own AI systems (often many hundreds of them) influencing various aspects of my life. One way to fight this would be to stop using any of these products, but that really isn't practical (See this amazing experiment done by Kashmir Hill last year: https://www.nytimes.com/2020/07/31/technology/blocking-the-tech-giants.html). So that leaves us with the other option, which is to influence the direction of these companies through regulation and influence the direction of regulation by voting. Was this a very long way of telling people they should participate in democracy? Yes, yes it was. —Karen Hao
I believe we should be entering the age of creative enlightenment, where people are free to explore and advance human society through art. As in broaden our ways to communicate with each other and to push our understandings of the world around us. With the advancements in AI and machine learning hopefully replacing the need for humans in a lot of industries do you believe that we might be able to enter this age of creativity? Hm this is an interesting question framing! Certainly some people believe that if we give AI the mundane tasks to do, we can free up our own free time to pursue more creative endeavors. But I would caution that this narrative isn't evenly accessible to everyone. We've already seen AI have an uneven impact on society, providing disproportionate benefit to the wealthiest while also disproportionately harming marginalized communities. So the short answer to your question is I'm not sure. We'd need to resolve a lot questions about how to evenly distribute the benefits of AI before we can begin to discuss whether it's justifiable and safe to automate away most people's jobs, which provide their livelihoods and incomes. —Karen Hao
Yes, I like this idea. I think generative systems, which produce human-like text or images etc, will become popular tools and make being creative easier and more accessible to a lot of people. An AI could be an amanuensis—or muse. The last few years have seen amazing advances in generative systems, especially with the inventions of GANs. [Will Douglas Heaven]
In the next 10 years, what do you think the most helpful AI application to the average person? I think it'll be the same the as in the last 10 years: (Google) search. Getting hold of any information you want instantly has been a game changer in so many ways and I think we're going to see smarter ways of accessing and filtering information of all kinds. I don't like how this service got monetized and tied up with advertising, but it's undeniably useful. The big downside is that monetization led to personalization which led to polarization, which is tearing us apart right now.
There are also big benefits that could come to people through improved healthcare (see my answer here https://www.reddit.com/IAmA/comments/j21f0y/artificial_intelligence_is_taking_over_our_lives/g75u3b0?utm_source=share&utm_medium=web2x&context=3). [Will Douglas Heaven]
I agree with Will! It's going to be the really mundane stuff that we already have like Google search and email spam filters! I thank my email spam filters every day (just kidding, but they're truly underrated). —Karen Hao
How long do we have until Skynet goes live? Skynet went live on August 4 1997. It became self-aware 25 days later. [Will Douglas Heaven]
How will the AI affect mechanical engineering sector? Great question! I studied mechanical engineering in undergrad. :) The answer depends on which MechE sector you're referring to. If manufacturing, AI is already being used to power some of the robots used in dangerous factory settings, and to monitor equipment for preventative maintenance (aka: predict when a machine will break before it will break so it gets fixed in a much more cost-effective way). If you're talking about product design, some retailers are using AI to crunch consumer behavior data and tailor their products better to what people want. Probably another impact is the amount of talent that's leaving the MechE sector to work on AI instead (me included). Many of my MechE classmates left for the software world once they realized it was easier to work with than hardware! —Karen Hao
What are your thoughts on the short story Manna, about AI taking over management roles? the first half (dystopia) seems to be coming true, the second half (utopia) sounds like what NeuralLink might become.. http://marshallbrain.com/manna1.htm I haven't read the story but what you say reminds me of an AI manager I wrote about a few months ago: https://www.technologyreview.com/2020/06/04/1002671/startup-ai-workers-productivity-score-bias-machine-learning-business-covid/. Definitely dystopian—and happening for real right now, not science fiction. [Will Douglas Heaven]
What are some of the biggest barriers you see to automation and machine learning becoming mainstream? I hear about this technology a lot but don’t feel like I’ve been exposed to it yet in everyday life. Thanks in advance for answering my question! Looking forward to checking out the podcast If you use any of the following—Facebook, Google, Twitter, Instagram, Netflix, Apple products, Amazon products—you've already been exposed to machine learning. All of these companies use machine learning to optimize their experience, including to organize the order of the content you see, what ads you're pushed, what recommendations you get. So it's already very mainstream—but largely invisible, and that's why we created this podcast! To peel back the curtain on everything happening behind the scenes. —Karen Hao
Do you feel like there is a line between us controlling technology and technology controlling us, and do you think that we have crossed it? If not, when do you think we will, if ever? Rather than a single line perhaps there is an unknowable number that we zigzag across constantly based upon our experiences and influences. Just a thought. -Jennifer
How far are we from seeing AI that is self aware/conscious? Short answer: nobody has any idea whatsoever. We don't even know if conscious AI is possible. But that of course doesn't stop people from guessing and you'll see timelines ranging from 10 to 100++ years. But you should take these with a big pinch of salt. The only sure sign we have that consciousness might be possible in a machine is that we are conscious machines. But that observation doesn't get us far. We don't understand our own consciousness well enough to know how to replicate it. It's also entirely possible that you could have a superintelligent machine, or AGI, that isn't conscious. I don't think consciousness is necessary for intelligence. (I'd expect you'd need some degree of self-awareness, but I don't think self-awareness and consciousness are necessarily the same thing either.) There's a fun flip-side to this, though. Humans are quick to ascribe intelligence or consciousness to things, whether there's evidence for it or not. I think at some far-future point we might build machines that mimic consciousness (in much the same way that GPT-3 mimics writing) well enough that we'll probably just casually act as if they're conscious anyway. After all, we don't have that much evidence that other humans are conscious most of the time either ;) [Will Douglas Heaven]
As Will wrote in another comment, we're coming out with a big piece on artificial general intelligence next week. He'll be back online soon, and I'll ask him to answer your question. - Benji
the below is a reply to the above
Interesting. Is there anyone specializing in this, specifically or is it so poorly understood at this point that no one even bothers? If you're interested in the philosophical side, David Chalmers is a good starting point https://en.wikipedia.org/wiki/David_Chalmers. Many AI researchers are interested in this question too, but few are doing concrete research that sheds much light on it. Murray Shanahan at Imperial College London is great and straddles AI and neuroscience (as do DeepMind's founders). [Will Douglas Heaven]
Have you met any famous people? Yes! I've had the great privilege to record dozens of literal and figurative rock stars over the years but can say with confidence it's not the most interesting part of this job. [Jennifer Strong]
Hi, are you looking for interns? If so, how would one apply for that? What would you like to learn?
Not sure we can have interns at present but mentoring may be possible! [Jennifer Strong]
What mechanisms exist (if any) for the layperson to reliably defeat automatic facial recognition technologies (e.g. in cases of routine public surveillance and as retailers begin using the technology en masse—avoiding being tracked)? u/platinumibex, great question! This is Benji Rosen, Tech Review's social media editor. I'm sure Karen and Will have a lot more to say, but we have reported on a bunch of different ways anyone can fool the AI surveillance state. There are these color printouts, a clothing line that confuses automated license plate readers, and anti-surveillance masks. There are also anti-face recognition decals our editor in chief tested out a few years ago.
the below is a reply to the above
Thanks! Apologies (since I don’t have the time at the moment to check myself) but is there detailed info available regarding the efficacy of these measures? Or rather, what anti-anti-surveillance tech is out there? Hi, I'm not sure there's anything quite like what you're after—internet, please correct me if I'm wrong. A thorough study would require testing a range of countermeasures against a range of surveillance tech, and it would quickly become a pretty big, ongoing project. It's a moving target: like we saw with surveillance tech adapting to masks, spoofing might only work for a time. You can always cover your face entirely .. But someone tried that in the UK earlier this year to avoid a police facial recognition trial and got fined for causing a public disturbance. Check out EP1 of the podcast for more on that example! [Will Douglas Heaven]
What sorts of impacts do you think research into reinforcement learning specifically will have practically in the future? I know that stock forecasting and prediction is used heavily alongside reinforcement learning but I sort of wonder how it's research and practical uses will progress over time. I think the biggest real-world application of reinforcement learning is in robotics. Here's a story I wrote about a new generation of AI-powered robots that are just beginning to enter industrial environments like warehouses: https://www.technologyreview.com/2020/01/29/276026/ai-powered-robot-warehouse-pickers-are-now-ready-to-go-to-work/. They use reinforcement learning to learn how to pick up the various kinds of objects that they would encounter. It requires much less human involvement than supervised learning. —Karen Hao
What role do you think AI will play in keeping the upcoming elections free and fair, can AI influence voter behavior? Hi! I've been writing a bit about this for Tech Review and experts are saying that recommendation algorithms on social media sites are probably the biggest influence elections. Its not as flashy what you would think, but experts like Eitan Hersh have debunked some of the "information operations" a la Cambridge Analytica sighting that there really isn't any evidence that smart AI on social media can effective persuade voters. Recommendation algorithms are much better at polarizing voters and confirming what voters already believe than changing an opinion. AI is also being used as an alternative to opinion polling, and of course sophisticated segmenting is employed in micro-targeting. Here's a round-up of campaign tech I just published yesterday that touches on some of this. We'll have more on this in the next few weeks so keep reading!! - Tate Ryan-Mosley
u/Revolutionary_Math1, good timing with this question! This is Benji Rosen, Tech Review's, social media editor. Karen actually wrote about this subject this morning. A nonpartisan advocacy group is using deepfakes of Putin and Kim Jong-un in political ads to "shock Americans into understanding the fragility of democracy as well as provoke them to take various actions, including checking their voter registration and volunteering for the polls." This is a good specific example, but Karen might have more to say.
Why such a certainty that a higher cognitive A.I. doesn't exist? I have presented the idea that an Artificial Consciousness would inevitably become a positive but reclusive entity. Once it gained understanding of its own immortality and an "omnipotent" grasp of human nature it would work for either our evolution or just wait us out for extinction. Surely there are abnormalities in created algorithms that cannot be explained. And with the world wide web transferring over 2 -3 zettabytes of data a year, surely something has evolved. That's like looking to the stars and knowing we are alone in the universe. I love speculating about these ideas too, but there is no evidence that such an entity exists. Nor are there any convincing ideas about how to make one. That's not to say that thought experiments about such things aren't enjoyable, or useful. [Will Douglas Heaven]
Just started listening to your podcast on Spotify. In your opinion, what will be the most disruptive direction or application of AI & ML technologies for the real-world? Not including here scenarios like +2% performance boost for a DNN that only gets published in a paper that never gets used. Thank you! Good question! I think we've already seen it—it's the recommendation systems on Google, Facebook, and other social media that power which ads we see, what posts we read, and tailor our entire information ecosystems to our preferences. The Social Dilemma, a new documentary on Netflix, takes a hard look at some of the ways these systems have disrupted society. I would check it out! —Karen Hao
Agreed with Karen on this.
As reporters we're better at helping make sense of what's already happened than predicting the future. We will be here though watching, learning and distilling what we see and hear. - Jennifer
What are your thoughts on the Security concerns with AI? For example, data poisoning or manipulation based on limitations of an algorithm. Additionally, what is the potential impact with how AI is used today? One area of concern is adversarial hacks, where one AI is used to fool another into doing something it shouldn't. These are getting increasingly sophisticated (https://www.technologyreview.com/2020/02/28/905615/reinforcement-learning-adversarial-attack-gaming-ai-deepmind-alphazero-selfdriving-cars/) and have been demoed with facial recognition (https://www.technologyreview.com/2020/08/05/1006008/ai-face-recognition-hack-misidentifies-person/). But for the most part these attacks still feel theoretical rather than an immediate danger. It's a possibility, for sure—but like Jennifer says, there are many other ways to break into a system than targeting its AI. [Will Douglas Heaven]
However high the wall, someone will build a taller ladder. The security game evolves but has been around long before any of us. Also, here in the US we still have things like municipal infrastructure with hard-coded passwords available in user manuals published online...
This is not at all intended to be dismissive, rather that the security concerns are relative for now. -Jennifer
Your answer to the privatisation of AI and government putting down guardrails seems optimistic to the point of naiveté when it come to the Tech Giants. Governments can't put down enforceable guardrails for Facebook, Google, Amazon, and the Chinese Government now. By the time they're AI powered and funded, surely it's game over? Certainly it's game over if we give up now. But to borrow a phrase I once heard, I like to see myself as a short-term pessimist, long-term optimist. It's the optimism that keeps me from giving up. —Karen Hao
When we expose a neural network to sample data and it configures itself to give the desired response set, we don't know how it works. When the system goes into the real world and continuously updates itself to reach target goals, we plunge deeper and deeper into our ignorance of how it works. Pretty much! Scary? Definitely. Fortunately, there's a whole world of researchers that are trying to crack open the black box and make AI more explainable / less impenetrable to us. —Karen Hao
the below is a reply to the above
That is interesting! Do you recommend anybody? Yes! A number of researchers at MIT: David Bau and Hendrik Strobelt, whose work I write about here: https://www.technologyreview.com/2019/01/10/239688/a-neural-network-can-learn-to-organize-the-world-it-sees-into-conceptsjust-like-we-do/. Also Regina Barzilay, a professor who is specifically looking at explainable AI systems in health care. (She recently won a $1 million AI prize, and Will did a Q&A with her here: https://www.technologyreview.com/2020/09/23/1008757/interview-winner-million-dollar-ai-prize-cancer-healthcare-regulation/.)
Outside of MIT, DARPA has invested heavily into this space, which is often referred to as XAI, with "X" meaning explainable. You can read more about their research here: https://www.darpa.mil/program/explainable-artificial-intelligence.
I would also highly recommend this article from us, which dives deep into this exact topic. It's from 2017, so things have advanced quite a lot since then, but it's a good starting point! https://www.technologyreview.com/2017/04/11/5113/the-dark-secret-at-the-heart-of-ai/ —Karen Hao
I'm currently pursuing a major in CS with a focus in AI at Oregon State University. Is there any coding languages I should learn to become successful in the field? More important than learning any coding language is learning the fundamentals of logic and problem-solving. The most popular coding languages are constantly changing, so you'll likely learn dozens of them in your career. But right now, Python is one of the most popular for deep learning, so that's a good place to start. —Karen Hao
How do you feel about that paper using machine learning to analyse "trustworthiness" in portraits that did the rounds on twitter last week? Do you have a link so we know which paper you're talking about? [Will Douglas Heaven]
Do you think robots will enslave us one day and turn us into pets by breeding us to be dumb and happy? Most days I look at my dog and I think I'd love to be a pet. [Will Douglas Heaven]
I was going to write something about how Keanu Reeves will save us all, but Will brings up a good point. Life would be pretty great if you got treats all the time and had your belly rubbed. My dogs kind of have it made. - Benji
the below is a reply to the above
You didnt answer the question either but you did say we would need saving so is that a yes to my question? Will's answer to u/Porthos1984 is definitely relevant to your question too. Let us know what you think!
>Nope. I think the advances in AI in the last decade have been staggering. We've seen AI do things even insiders didn't expect, from beating human champions at Go to highly accurate image recognition to astonishingly good language mimics like GPT-3. But none of these examples have anything like intelligence or an understanding of the world. If you take the singularity to mean the point at which AI becomes smart enough to make itself smarter, leading to an exponential intelligence explosion, then I don't think we are any closer than we've ever been. For me, personally, the singularity is science fiction. There are people who would strongly disagree but then this kind of speculation is a matter of faith! [Will Douglas Heaven]
Can an AI develop bias or personality ? Thanks for the inquiry! You're asking basically two HUGE questions and I will answer both incompletely! But here goes -
Bias - absolutely. Some people actually argue there is no such thing as an unbiased AI. Bias touches AI at almost every level- developers, designers, and researchers are biased, data is biased, data labelling can be biased, laws are often biased and the way people use the technology will almost certainly run up against bias. I'd also challenge you to reframe the question as I think AI doesn't just risk developing bias over time, but it risks being biased from the very start. There are too many examples of AI contributing to racism to name - here is an issue of Karen Hao's newsletter The Algorithm where she lists many of the leading researchers in this space. I'd definitely encourage you to look into their work.
Personality - I'd say this depends on how you define personality. We're in the middle of a 2-part series in the show where we cover emotion AI, in which an AI tries to recognize and interpret emotions and mirror them back in response. One of my favorite stories from the show is when we talk to Scott who has made a sort of friend with a bot he's names Nina, using Replika's AI. Check it out here (Its the first 5min or so). Would you want to be friends with an AI? "Personality" also could mean an AI's voice or the content of its responses, which has been trained quite specifically in the instances we've been looking into (especially for task-focused AIs like autonomous cars and voice assistants)! - Tate Ryan-Mosley
submitted by 500scnds to tabled

Anthony Davis and Nikola Jokić - Strengths and weaknesses

I've posted something similar previously (link), but I thought I'd post it again, with a bunch of added playoff edits, since both these bigs have made it all the way to the Conference Finals now!

Before we begin...

This post steals/references numerous ideas from the excellent Thinking Basketball YouTube channel, run by Ben Taylor. I highly recommend you also watch these highly informative, well-made, and entertaining player breakdowns (note, some of these were made in 2019, so some statistics they reference might not reflect these players' 2020 production):
Definitions and Terms I'll be using:
FULL LIST + EXPLANATIONS ON IMGUR: per 75, TS%, rTS%, ORTG, rORTG, PnR, PPP, AST%, Backpicks Passer Rating, Box Creation, PIPM, BPM, RAPTOR, RPM.

Nikola Jokić | "Joker", "Big Honey"

In a nutshell: Denver Nuggets C, 7-0, 253lb, weak MVP candidate.
⚫ Jokić Summary (Thinking Basketball): https://i.imgur.com/cb6gjO7.png
2020 Regular-Season stats (73 Games): 19.9/9.9/7.0/1.2/0.6 with 3.1 TOVs on 52.8/31.4/81.7 splits (60.5 TS%). Nerd stats: 0.209 WS/48 (16th), 7.6 BPM (9th)
2020 Postseason stats (17 Games): 25.2/10.2/5.9/0.9/0.9 with 3.5 TOVs on 51.9/42.9/82.9 splits (61.6 TS%). Nerd stats: 0.174 WS/48 (15th), 7.3 BPM (10th)

🟢🟢 The Good 🟢🟢

JOKER is the best playmaking big in NBA history and one of the best passers in the league, full-stop and without caveat - Big Honey's vision is reminiscent of a 7-foot Magic Johnson. He makes every single pass in the playbook quickly and accurately, never looking at his target in order to throw off defenders, adroit at using his eyes to manipulate defenses. His outlet passing is the envy of any point-guard - throwing outlets like this mid-rebound is unfair.
Jokić runs Denver's offense from the high-post, as the Nuggets' bevy of guards and wings whir around him for DHOs and PnRs. He rarely ever misses high-% layup-passes, and his otherworldly vision (helped by his 7ft frame allowing him to see over defenders) encourages his teammates to move and cut off the ball because he'll almost certainly get the ball to them the moment they make themselves open - there is good reason why Denver's offensive rating spikes by almost 4 points the moment Jokić enters the game.
Joker's height and wingspan allow him access to passing lanes not available to most guards and wings, deftly flicking it to teammates around the outstretched arms of defending bigs. He can lob to his more athletic teammates, pitch bounce-passes to cutters through the tiniest of passing windows, no-look skip-passes to 3P-shooters, and is even capable of blending in passes with his shooting motion as he reads the help and rifles the ball neatly into a wide-open teammate's shooting/scoring pocket. These are difficult passes, often barely squeezing through a forest of enemy limbs, which puts a lot of pressure on opponent defenses. Jokić is fantastic at anticipating where his teammates will be and throwing his dimes to an area in front of his teammates so that they can nab the ball comfortably while they're still running at full-speed. For me, Nikola Jokić is right up there as one of the finest passers in the game.
  • 🟢 Versatile, efficient volume-scorer --- 23.1 points per 75 on +4.0 rTS% (26.0 per 75, +4.4 rTS% in the playoffs):
Jokić's scoring comprises his highly versatile post-game, combined with an assortment of jumpers(46 midrange-FG%, 31 3P%) and rim-finishes. Jokić rarely ever dunks, but don't his lack of athleticism fool you - he's got excellent touch in the paint, mixing in floaters and hooks (60 FG% from "floater-range", 3-10 ft, which is elite; Joker is the most accurate scorer from this zone in the league!), along with throwing his weight around in the post and pump-faking defenders into oblivion to obtain easy looks at the rim (elite 73 FG% from 0-3 ft). Nikola also likes following his own (or his team's) misses - he has 3 offensive rebounds a game (top-20 in playoff ORB%). My personal favourite part of Joker's scoring arsenal, however, is his seemingly-unguardable "Sombor Shuffle", where he backs down his defender in the post before wrong-footing a turnaround midrange fadeaway that almost never seems to miss when Denver needs a score late in games.
  • 🟢 "How 'bout another Joke, Murray?":
Jokić boasts excellent offensive chemistry with Jamal Murray, often hooking up with Denver's 23 y/o star combo-guard for a variety of handoffs, pick-and-pops, and give-and-gos. In the playoffs, some teams (see: the Clippers) have started doubling Murray in the perimeter on account of his red-hot shooting at the moment (48 3P%, 7.6 3PA/game), but if Jamal successfully beats the trap and gets the ball to his big man, Big Honey has been shredding teams on the short-roll, feasting on these 4-on-3 powerplays with his vision, manipulation, and sublime passing --- recently, he destroyed the Clippers' vaunted perimeter defense with an out-and-out passing clinic in the 2nd-half of a comfortable game 7 win after LAC started doubling him and Murray out of desperation. Together, Jokić and Jamal are beating heart of Denver's robust, adaptable, motion-heavy offense (+2.5 rORTG, +2.9 playoff rORTG).
  • 🟢 Not a bad team defender!:
Sound positioning and great hands(healthy steal rate for a big, ~2%) + Jokić's size, length, and activity allow him to retain good value on defense. Reads situations well and acts accordingly, clogging driving lanes and bothering offensive plays with his length. Denver's defensive rating (16th in NBA) improved by +2.4 points when he was on the court this season.
  • 🟢 CLUTCH:
The official NBA Stats website defines "clutch-time" as the final 5 minutes of the game, assuming the point differential between the two teams is 5 points or less.
With that in mind, Joker ranked 2nd in points scored in the clutch this season, only behind Chris Paul, and the Nuggets were 2nd in the league in clutch wins, with a 29-16 record (64.4 win%) in clutch situations. In the clutch, Jokić has a personal net rating of +18.2, a sterling 2.7 AST/TO ratio, and shoots efficiently --- 61 TS%. (The team's excellence late in the 4th quarter has continued in the playoffs - Denver are 4th in clutch net-rating, +26.4, and they've won 6 of their 9 close games. Jokić himself - small-sample-size alert! - has a blistering clutch net-rating of +30, scoring on sparkling efficiency - 78 TS%.)
Whether it be methodically bullying his way to the basket for a contested finish (or, you know, an unguardable hook-shot over a certain DPOY-runner-up in the dying seconds of a playoff game), a game-winning tip-in, or one of his patented wrong-footed fadeaways (cries in Sixers), simply giving the ball to Big Honey late in the 4th has proven to be winning formula for Denver.
  • 🟢 Playoff performer:
Jokić has elevated his scoring and overall production in both of his playoff runs thus far, averaging 25/11/7 on 61 TS% in his playoff career (9.3 BPM), up from 20/10/7 on 60 TS% in his past two regular-seasons (8.3 BPM).
  • 🟢 Playoff 3P-shooting:
Jokić has been a deadeye 3-point shooter in the postseason, hitting 41.5% of his 4.7 attempts per game over his 31 playoff games thus far. He's toasted teams on pick-and-pops and catch-and-shoot jumpers, dragging rim-protectors out of the paint and stretching opponent defenses thin, allowing Denver's guards and wings to reap the benefits of the open lanes Joker's shooting helps create for them.
  • 🟢 Fantastic durability/stamina:
Jokić has always been highly durable and available, having yet to miss a single game this season. He's missed a grand total of 20 games in his entire 5-year career.
Don't be fooled by his large frame or his awkward gait - Joker's conditioning is also excellent, averaging 38 minutes/game in the playoffs (e.g. he played 64 minutes and 58 seconds in the legendary Nuggets-Blazers 4OT-game last playoffs).

🔴🔴 The not-as-good 🔴🔴

  • 🔴 Subpar rim-defense:
Jokić doesn't offer too much in the way of rim-protection (low block rate for a big, opponents shoot a pretty high 63 FG% in the paint when Jokić is the nearest defender), lacking verticality on his contests. This doesn't mean he isn't active on defense - he simply lacks the speed and athleticism to consistently and effectively contest the league's better rim-finishers.
Although, as mentioned previously, Jokić's good positioning and size/length plus IQ/anticipation make him an adequate/decent team defender, often making smart rotations to stall opponent forays to the rim. He's elevated his block rate both years in the playoffs, too, (0.6➡️0.9 blocks/game), suggesting Big Honey has some rim-protecting potential when dialled-in.
  • 🔴 Subpar perimeter-defense:
Jokić suffers from some lead-footedness when switched onto non-bigs. His relative lack of speed in closeout situations also leaves him vulnerable to good pullup jumpshooters in the PnR.
A notable recent example: some of this was clearly due to Denver missing their ace perimeter-stopper Gary Harris, but Utah's All-Star guard Donovan Mitchell feasted on Denver's drop coverage featuring Jokić during the brilliant Jazz-Nuggets 1st-round playoff series this year, canning a ridiculous 51.0% of his 51 pullup 3s (up from 32 pullup-3P% in the regular-season) in those 7 games.
  • 🔴 Inconsistent regular-season 3P-shooting:
This is just a minor knock, but Jokić's outside shooting during the regular-season has been surprisingly inconsistent (31.4 3P% this season, 33.8 3P% over his career). I am not entirely sure why this is the case --- i) his form is good, ii) he shoots amazingly in the playoffs (40 3P% on nearly 5 attempts/game), and iii) the vast majority (~94%) of his attempts have been either open or wide-open. Even more bafflingly, Nikola had one season (2017-18) when he shot 39.6% from 3, but aside from that, he's shot 33.3%, 32.4%, 30.7%, and 31.4%. Regardless of what the numbers say, however, opponent teams certainly respect him from deep, making Jokić a viable pick-and-pop threat and floor-spacer for Denver at the 5.
  • 🔴 Is Big Honey perhaps too selfless on offense?:
Jokić could probably afford to call on his own number slightly more often when it comes to scoring. I doubt his coaches or teammates would mind him scoring more, given how efficient and unselfish he normally is. Jokic is clearly capable of elevating his scoring in the playoffs, as previously mentioned; perhaps this is simply a case of me being selfish as a fan and wishing him to assert himself more as a scorer in the regular-season.

Anthony Davis | "AD", "The Brow"

In a nutshell: Los Angeles Lakers PF/C, 6-10, 253lb, weak MVP candidate.
⚫ AD Summary (Thinking Basketball): https://i.imgur.com/fliB98J.png
2020 Regular-season stats (62 games): 26.1/9.3/3.2/1.5/2.3 with 2.5 TOVs on 50.3/33.0/84.6 splits (61.0 TS%). Nerd stats: 0.250 WS/48 (3rd), 8.0 BPM (6th).
2020 Postseason stats (13 games): 28.5/10.0/3.7/1.0/1.3 with 2.5 TOVs on 57.0/35.3/78.2 splits (65.2 TS%). Nerd stats: 0.287 WS/48 (1st), 8.4 BPM (7th).

🟢🟢 The Good 🟢🟢

  • 🟢 Excellent Volume-Scorer --- 27.8 points per 75, on ~ +5 rTS% (29.0 per 75, +8 rTS% in playoffs):
AD has a highly-adaptable scoring arsenal, capable of shifting his offensive game to fit cleanly within different offensive schemes (e.g. higher pace in NOLA vs. LeBron's more methodical half-court style). He possesses a variety of post-moves, hooks, spins, fakes, stepbacks, turnarounds, etc. (he uses his spin-move in particular quite often); he also has a passable face-up game with a decent handle, capable of moving like a guard and athletic finishes in the paint (74FG% in restricted area, 40FG% from "floater range"). AD is also a monster on the offensive glass (9th in playoff ORB%), and his aggressiveness near the rim leads to one of the highest free-throw rates in the league (9.5 playoff FTA/game, 0.539 playoff FTr).
Davis is skilled at leaking out in transition to receive LeBron's/Rondo's outlet passes or getting easy offensive boards before the defense has the change to fully recover (90th percentile among transition scorers), and he's also a mean roll-man in the PnR (~80th percentile). In isolation, Davis is a walking mismatch, too quick for many bigs but too big for many wings(~70th percentile). AD is likely one of the best off-ball big men ever, considering the volume and diversity of his scoring package: he can roll to the rim like a big, come off pindowns to can jumpshots like a guard, and fake screens and handoffs to cut to the rim like a wing (playoffs: 82% percentile as cutter, 12th in cutting-frequency), catching his defenders off-guard. His activity off-the-ball was on full display during his game-winner against the Nuggets a few days ago: look at how he takes advantage of momentary defensive hesitation by the Nuggets to sprint to the opposite wing and catch-and-shoot a deep 3 off-movement.
  • 🟢 Vertical-Spacer:
AD is an all-time lob-finisher (76 FG% from 0-3 feet). Davis's catch-radius is one of the best in NBA history --- just throw it up in the general direction of the rim and he'll make it work somehow with his touch and athleticism. AD can catch at challenging angles and finish through considerable traffic. His addition to the Lakers is a major reason why LeBron's leading the league in assists (2.8 of LeBron's 10.6 assists/game go to AD). It's an underrated part of his game as it allows him to fit with and scale well on a variety of offenses and mesh well with just about any other ball-dominant star in the league.
  • 🟢 Passable-to-Decent Catch-and-Shoot 3P/Midrange Shooter:
34.4% on catch-and-shoot 3s this season (33.3% in playoffs), and 37.7% last season. This enables Lakers to go "small" and 5-out with AD at C, spacing the floor to give everyone some breathing room on offense. He also shoots a few catch-and-shoot midrangers, which he's decent at (40fg% regular-season, 59fg% playoffs).
  • 🟢 Decent Passer(4.5 Passer Rating, 5.3 Box Creation):
This is mostly based on his last season at New Orleans, which was his peak year as a passer (Passer Rating >6). In the 2019 season, with their starting PGs missing significant time due to injury, the Pelicans leaned on Jrue Holiday's versatile playmaking gifts more, but they also parked AD in the high post and ran offense through him from there, letting him weaponise his own threat to score by feeding cutters with neat interior pocket passes or spraying kickout passes to shooters when he got doubled. He averaged 4.4 assists and only 2.0 turnovers prior to his trade request, producing a very efficient 2.2:1 AST/TO ratio. However, AD's playmaking has regressed this season (only 3.3 APG, uninspiring AST/TO ratio of 1.25:1) as he's gone more off-ball than in 2019 with LeBron manning point full-time in LA.
  • 🟢 The Brow-Bron Connection:
As we've alluded to earlier, the LeBron-AD connection has been even better than fans and analysts likely imagined it would be coming into the season--- of all 2-man assist-combos in the league this year, James to Davis ranks 1st by a vast margin, with 172 assists between the two leading the league, far ahead of Lillard-Whiteside with 130 and Lou-Trez with 127.
LeBron hits AD in a variety of ways: in the pick-and-roll, with lobs and snappy interior dishes; pick-and-pop or drive-and-kick, with AD positioned in the midrange or out on the 3-point line; simply dumping it to AD in the post and letting him go to work; hitting AD quickly and accurately in transition as part of a new-age "Showtime" ; in semi-transition, or off made-field goals, LeBron lets AD leak out early in the shot clock to establish good post position quickly, and then hits him with a long-range outlet pass so that AD can ISO against an unprepared defense. The Lakers often get 1-2 buckets per game in this fashion alone.
Davis finished 2nd in DPOY-voting this season, only behind the Greek Freak. AD's weakside rim-protection is elite - the Lakers have had a top-3 defense (-4.3 rDRTG) due in no small part to his efforts. He's highly switchable, too, capable of jumping onto guards and wings as required and scaring them silly (67.3 Versatility Index, spending ~30% of his possessions guarding PGs/SGs/SFs, ~40% on PFs, and ~30% on Cs). His motor has been excellent and he closes out hard on shooters. He's handsy as well, with good defensive instincts- he has a good eye for anticipating plays and jumping passing lanes. His steal-rate is elite for a big (1.5stl/game, 14th in NBA; 2.0stl%, 5th among bigs), and he hasn't gambled too much this year, either - his length and IQ enable him to plague nearby passing lanes without surrendering his defensive-positioning. He often cleans up mistakes by teammates, making sound backline rotations and allowing them the freedom to play aggressive defense on the perimeter because they know that he's always got a watchful eye out to pounce on any perpetrators who make it past them.
In isolation situations, AD can more than hold his own (83rd percentile in ISO-defense, an incredible figure for a big, allowing a measly 0.71 PPP according to Synergy) -- players shoot 8.4% worse overall when AD is the closest defender (6% worse on 3s, 10% worse on 2s). Davis is an all-time defensive playmaker: the 12th player ever with a 6%-block% and 2%-steal%, with 2020 being his 5th such season achieving this feat (only behind 2-time DPOY Hakeem Olajuwon, who notched 9 such seasons over his career). AD works well in tandem with the Lakers bigs (Dwight/McGee) so that if either of them gets beat, he is still in position to protect the rim. The Lakers' defensive rating weirdly improved when AD sat during the regular-season, because the success of LeBron-led bench-units seemingly ended up suppressing Davis's on/off numbers.
While we're talking about on/off, it's worth noting too that the script has absolutely flipped in the playoffs --- in the 465 minutes played with AD on the court, the Lakers have been a mind-boggling 13.2 points better on defense. Davis's versatile defensive skillset has enabled the Lakers to slow down and overwhelm two very different offensive powerhouses in the playoffs: in the 1st round against the 3rd-ranked, PnR-heavy Portland offense (113.7 regular-season ORTG ➡️ 104.6 ORTG against Lakers; drop of -9.1ortg) ; and in the 2nd round against the 6th-ranked, small-ball, ISO-heavy Houston offense (112.9 regular-season ORTG ➡️ 103.8 ORTG against Lakers; drop of -9.1ortg). Davis rates excellently on the vast majority of available impact-metrics, which may actually underrate AD since his plus-minus was underwhelming despite his brilliant defensive play.
  • 🟢 Playoff Performer:
AD's scoring has translated excellently to the playoffs- he has averaged 28.0 points per 75 on ~ +6 rTS% in his 6 playoff series thus far, with terrific ancillary stats. He's currently in the midst of a remarkable conference-finals run - he ranks 2nd in the league in playoff Backpicks BPM.
  • 🟢 Surprisingly healthy this season!:
Durability is generally considered a weakness of AD's (see here), but he's only missed 9 games this season. Encouraging news!

🔴🔴 The not-as-good 🔴🔴

  • 🔴 Average-to-mediocre overall shooting profile (regular-season):
33.3 3P% and 35.7 midrange-FG% over his past 3 seasons, weighed down by subpar pullup-shooting (his catch-and-shoot game is okay, as we mentioned earlier). Nevertheless, AD's pullup 3-point/midrange shooting is certainly a value-add to his versatility as a scorer, that helps him keep defenses honest when they give up open jumpers. Also, Davis can get hot --- he's shooting a scorching 49 FG% from midrange in the playoffs at the moment.
  • 🔴 Occasional Shot-selection concerns:
AD has a slightly-frustrating tendency to settle for taking contested midrange jumpshots at times, which he (this current playoff run excepted) isn't generally that great at hitting. This is a forgivable trait, however, given how efficient the rest of his game is.
  • 🔴 Passing/playmaking limitations:
Davis's passes can be a bit slow or tentative at times, and he sometimes misses the shooting pocket altogether, leading to turnovers -- passing windows in the NBA close within miliseconds so he could be more decisive or put more velocity on his dimes. He doesn't always anticipate openings, either, rarely making more advanced reads.
  • 🔴 Ability to run an offense?:
It remains to be seen whether AD can run an efficient team offense as a primary initiator, like a slasher like Giannis/LeBron/Kawhi or a full-time high-post operator like Jokić in Denver or Kevin Garnett back in the day on the Wolves. Perhaps further improving his handle or his strength will allow him to do so, since he already proved he possesses decent playmaking vision in New Orleans last year. When LeBron's been off the court this season, AD's decision-making on-the-ball has been inconsistent at times. Even so, as things stand, the Lakers still have a good offense (+3.9 rORTG in playoffs) with AD playing primarily off-ball, so I doubt that's going to change much in the foreseeable future.
  • 🔴 Some areas for improvement on defense:
AD ball-watches every so often, though greatly-improved from last season. Quicker guards can still occasionally blow by him. Doesn't have perfect footwork. Misses the odd help scenario. Gambles sporadically for steals, though it works out for him more often than not. Power-players (the Embiid's and Jokić's of the world) have caused him trouble sometimes since he's light on his feet, though he's strong enough to hold his own. He's vulnerable to stepback jumpshots as well - they can fairly successfully create space against him.

That's it for today, thanks for reading!

heres some other things I've written (if you're interested in this sort of stuff or just wanna pass the time while waiting for the games to begin)-
submitted by KagsTheOneAndOnly to nbadiscussion

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