Jarad Johnson retweeted
AI productivity gains are showing up, but only in ~15% of jobs.
The three heaviest AI adopters (information, professional services, finance) went from a 2.2% productivity trend to 5.0% since 2022.
The rest of the economy: 0.9% to 1.4%.
Jarad Johnson retweeted
public speaking is a weird catch-22: it's hard to feel confident without evidence that you can be good at it, but it's hard to get that evidence if every talk feels like torture.
the first time you give a talk will be the worst version of that talk. you are learning, live, how each part lands with the audience, which means you are working out the content while also trying to improve your speaking skills.
rehearsing in front of the mirror ahead of time helps but only to an extent. the reason public speaking is hard is because it feels deeply unsafe. practicing without stakes is not really practicing the hard part. you need exposure to the vulnerability of being perceived.
this is why, if someone on my team is working on their public speaking, I find it helpful to contrive situations where they need to give the same talk repeatedly (like 5+ times). they are usually stressed out for the first 1–3 times. but with each rep, they get more comfortable with their delivery. by the 5th time they can start to have fun with it, workshopping new riffs on the fly. the confidence in the content allows them to settle into the delivery.
I learned this accidentally when I had to deliver a product training in all 8 of Dropbox's global offices. I gave the same talk, which included a live Q&A, about a dozen times. I went from very terrified of public speaking to much, much more comfortable with it. and it gave me the confidence that I could improve even more if I kept finding reasons for people to hand me a microphone and put me in front of a room.
if you're trying to come up with a talk you could give 5+ times, work backwards from something that others in your organization (or at other companies) would benefit from learning and that you'd be well-positioned to teach them.
I wrote more about this here: hils.substack.com/p/hate-sel…
Most people don't know this about me, but I've long had really bad stage fright. I'd get extremely nervous giving talks, speaking in big meetings, being in the spotlight. It's still a problem, but it's gotten a lot better in the last couple of years.
For those struggling with this too, three things that made a real difference for me:
1. Ultraspeaking: ultraspeaking.com/. It's a unique approach to building confidence in public speaking, in a fun and low-stakes environment.
2. Beta-blockers: hims.com/psychiatry/proprano…. It quiets the body's physical anxiety so you can focus on what you actually want to say. Do your own research (and talk to your doctor), but it's felt like a miracle.
3. This advice from @tobi below, plus a few other mantras I repeat in my head that shift my mind from worst case to best case:
- "Look what I get to do!"
- "Don't perform. Be yourself."
- "Find the joy in it."
- "Dare to be dull."
- "I love public speaking!" via Tobi
If you've struggled with this too, anything you've done that has made a big dent? In case it may be helpful to others.
Jarad Johnson retweeted
If you've ever wondered why smart TVs are so cheap, this is why.
@log4j rooted his Samsung and found an always-on hot mic, automatic content recognition, geolocation, network mapping, ad targeting and user profiling, shared with Samsung's "400 partners".
A lot of it can be blocked in <15 min, wrote a basic guide below.
What your TV is doing
The main culprit is ACR (automatic content recognition). Your TV screenshots what's on screen, fingerprints it, and sends it home to build your ad profile. Samsung does it every 500ms, LG every 10ms [1].
What is insane: it happens on connected devices too.
Plug in your laptop, your console, your work machine, and your TV can fingerprint that via HDMI [1].
He also found that if your Samsung doesn't have a mic, it'll look for one from a connected soundbar or bluetooth device.
xitter.cf/log4j/status/211376224…
It's on by default, and you likely agreed to it on the setup screen you clicked through in 10 seconds.
Step 1: Turn off ACR
Samsung: Terms & Privacy → Viewing Information Services
LG: Live Plus
Vizio: Viewing Data
Roku: "Use info from TV inputs"
Sony/Google TV: Samba Interactive TV
Menus vary by model, but those are the names to look for. While you're in there, opt out of interest-based ads, reset your advertising ID, decline every optional privacy agreement, turn off voice recognition, and delete apps you never open.
Step 2: Give smart devices their own network
Put the TV, cameras, speakers and vacuum on your router's guest/IoT network. The logic is simple: these devices rarely get patched. If one gets compromised (getting drastically more frequent with AI), it shouldn't be able to see your other devices or home network.
Step 3: Block trackers for the whole house with DNS-level filtering
NextDNS (cloud-based) is easy and has a solid free plan. Pi-hole is a little bit more work if you prefer self hosting. For simplicity we'll focus on the former.
1. Sign up at nextdns.io (free tier is plenty)
2. Privacy tab: add a blocklist (OISD is a good bet) and turn on Native Tracking Protection for Samsung, LG, Roku, Amazon (see attached image)
3. Setup tab: copy your endpoint
4. Paste it into your router's DNS settings as DNS-over-HTTPS/TLS (or use the IPs + "Link IP" if your router only does plain DNS)
5. Bonus: block outbound port 53 except to your router. Some devices hardcode their own DNS to get around you
Then open the NextDNS logs and watch how often your TV phones home. It's eye-opening. If an app or update breaks, find the domain in the logs and allowlist it.
Why they do this
TV prices are down 97% since 2000 [2]. Most of that is better manufacturing and brutal competition. But once margins on the hardware hit zero, the cost moved to you.
In Q3 2024, Vizio lost $6.7M selling TVs and made $115.8M in gross profit from ads and viewing data [3]. They've said on earnings calls that they keep TV prices low to grow the audience they sell to advertisers. Walmart bought them in 2024.
This isn't a conspiracy theory either. Vizio paid $2.2M to the FTC in 2017 for tracking 11 million TVs without consent. Last December, Texas sued Samsung, LG, Sony, Hisense and TCL over ACR. Samsung and LG have since agreed to stop collecting that data without explicit consent [4].
TL;DR
1. ACR off
2. Ads + voice off
3. Smart devices on their own network
4. NextDNS filtering on the router
Sources:
[1] ACR study: arxiv.org/abs/2409.06203
[2] Cost of US consumer goods: aei.org/economics/chart-of-t…
[3] Vizio Q3 2024: sec.gov/Archives/edgar/data/…
[4] Texas v. Samsung: texasattorneygeneral.gov/new…
They are happy to use other people’s work to build models but you can’t use the models to reverse engineer.
Open models are very important.
Claude can no longer “Reverse Engineer Anything.”
Anthropic just quietly killed REA.
But Interesting timing.
After a few viral cases of people using Claude to reverse-engineer Samsung TV firmware and identify data-collection services, Anthropic appears to have restricted those reverse-engineering abilities.
This might be really great, but you can't trust demos from labs. Release models, not demos.
I have a suspicion that the interruptions will be infuriating.
We believe voice is the most natural way to interact with intelligence, so we created Dessa, the most authentic full-duplex speech model ever built. Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence.
block.xyz/dessa
Jarad Johnson retweeted
Dario — Thank you for taking the time to respond to my previous post. I think it's great when this kind of engagement happens in public rather than on company Slacks, and I hope to see more of it.
I agree that Anthropic isn't best modeled as a profit-maximizer. Your post gave several compelling examples of Anthropic taking competitive hits for safety, and insofar as my previous post suggested otherwise, that's on me. But I don't think I made my main point as clearly as I could have, so let me try again. It comes down to four key claims:
1. Anthropic seems to be racing at breakneck speed to build recursively self-improving superintelligence (RSI). By its own lights, that could kill billions of people or literally destroy the world.
2. Risking destroying the world is very hard to justify. It is only conceivably acceptable if serious attempts to put RSI under robust societal governance are failing.
3. Far from meeting that burden, Anthropic, when push comes to shove, often works to keep governments from tying its hands. It seems to care much more about preventing government overreach than about reducing the risk that it and other AI companies will destroy the world.
4. Even if the AEGIS Act really was an honest mix-up, as you suggest, that is itself a serious problem. It suggests Anthropic isn't treating the governance of this technology with anything close to the gravity it deserves.
In greater detail for those who want it:
1. Anthropic is racing to RSI, and by its own lights that is insanely risky.
Launching RSI could literally destroy the world. That's according to you, your co-founders, and most of your safety staff and capabilities researchers, not to mention many AI researchers outside your walls. You are intentionally trying to create generally intelligent systems more capable than all humans that you claim in six to twelve months “could be capable” of taking over the entire internet before we have the ability to reliably monitor, control, or align them.
“Succeeding” at RSI could kill or permanently disempower billions of people in the near future, including me and everyone I love. Yet Anthropic’s primary focus seems to be marshalling an immense amount of resources and talent in a race to get there first.
2. Risking destroying the world carries an enormous burden of justification.
I believe the vast majority of people do not want Anthropic to do this (to the extent they know what it's doing). Imposing even a modest chance of catastrophe on billions of people who never consented requires an extraordinary justification. The central one Anthropic has offered: someone will build RSI regardless, so it's better for a safety-focused lab to be at the front of the pack, using that position to support strong AI governance. (Other reasons Anthropic has given, like modestly accelerating improvements in healthcare or economic growth, don’t seem remotely proportionate to the risks Anthropic is imposing by its own lights.)
But that argument only works as a last resort. Racing to RSI is only conceivably okay if attempts to institute robust societal governance to manage that race are failing despite your best efforts. A lab that relies on this justification should be a strong, consistent supporter of efforts to enact governance that could bind it, including governance that could slow it and significantly constrain what it does.
3. Rather than supporting efforts at strong regulation, Anthropic has intervened to keep governments from tying its hands.
Anthropic has sometimes helped: it played a very helpful role in passing transparency bills in Illinois and ongoing efforts in Massachusetts, and I'm sincerely appreciative. But transparency is far from enough for a technology that will be the world's most powerful superweapon at best, and an uncontrollable swarm of lethally superintelligent agents at worst. When it matters most, Anthropic has often pushed for weak regulation.
The AEGIS Act is the most obvious example. No highly risky industry is regulated as anemically as AEGIS would regulate frontier AI: not nuclear, not banking, not aviation, not food safety, not the manufacture of explosives. In all of those industries, specialist regulators can address unsafe practices well before they cause harm. AEGIS would bar the federal government from intervening to block unsafe development or deployment of models until there is an "imminent risk" of catastrophic harm, and would require it to meet a demanding burden of proof in court. Worse, AEGIS would also prevent states from picking up the slack. This design makes perfect sense if you're a company trying to minimize the risk that the government can overly constrain you. It makes little sense if you want American democracy to govern frontier AI effectively.
This isn't the first time. The initial version of California's SB 1047 would have let the Attorney General sue to stop developers like Anthropic from imposing unreasonable risks of catastrophic harm. It would also have created a regulatory agency to help set safety standards. Anthropic objected, and helped get both provisions removed before ultimately offering some support for the bill (which I also genuinely appreciate). I’m not saying that Anthropic should have supported 1047 in its initial form; that’s a complex issue and I realize there were questions about whether earlier versions of the bill were less politically feasible. Still, in Anthropic's own words, it helped weaken the bill because "[t]here is a substantial risk that the bill and state agencies will simply be wrong about what is actually effective in preventing catastrophic risk, leading to ineffective and/or burdensome compliance requirements."
The same goes for New York's RAISE Act, whose initial version also would have let the Attorney General sue to stop unreasonable risks of catastrophic harm. Anthropic credits itself as a supporter of RAISE, but it did not support the bill while it was in the legislature, including when it nearly died. After the bill passed the legislature, Anthropic publicly critiqued it, saying "Any state proposals should be narrowly focused on transparency and not overly prescriptive."
Why does Anthropic consistently take the risk of clumsy government action far more seriously than its own repeated warnings that companies like Anthropic will literally destroy the world by racing to RSI?
4. Even if AEGIS was an honest mix-up, that is itself a serious problem.
Your response frames AEGIS as an early draft and a miscommunication. Perhaps you would have strengthened it and narrowed its preemption. (That wouldn't explain Anthropic's interventions to weaken SB 1047 or RAISE, but leave that aside.)
Suppose that's exactly right. A federal framework for governing RSI is one of the highest-stakes documents your company will touch. Your post admits Anthropic "could have handled [these matters] better," but its tone ("This kind of thing happens a lot in large organizations") doesn't reflect the gravity of this issue. Anthropic talks about the need for “operational excellence” in critical areas, and I have a hard time believing that a similarly cavalier attitude would be tolerated while Anthropic was negotiating a key compute deal or preparing its next large pre-training run.
In short
The justification for racing rests on Anthropic fighting for strong governance, and Anthropic's record on regulation points the other way. Together with its breakneck racing, that fits a much darker picture of the company than the one that seems to prevail among your employees. I hope that Anthropic reflects on this picture, supports stronger regulation, exercises extraordinary caution when advocating for weak regulation, and doubles down on its founding purpose of helping the world safely navigate transformative AI together, instead of prioritizing Anthropic’s ability to win a race that imposes intolerable risks on everyone alive.
Thank you for this, @_NathanCalvin. I appreciate and am a fan of the investigative work you’ve done on behalf of AI safety and believe your comments are coming from a constructive, honest place, and that it benefits the public to have people whose job is to scrutinize the actions of frontier AI companies. I think something would be wrong if companies of the size of Anthropic didn’t get harshly criticized basically every day; strong antibodies against corporate power are a healthy feature of a free society, and especially so when issues of the gravity of the one we’re facing are at play. I also do agree that some of the examples you cite were mistakes by Anthropic.
That said, I disagree with the thrust of your post. At the core, a good fraction of the things you criticize are consequences of Anthropic’s basic theory of change that we have held for many years. Our strategy has always been what I’ve called the “race to the top” — by showing how it’s possible to build the technology responsibly, we can raise the bar for the entire industry. The forces that drive the race to the top are hugely more effective if the company practicing them is at the frontier; that’s one lesson I’ve learned repeatedly. And looking at that strategy as a whole, I’m proud of our track record and stand by it.
I believe that if we take a list of things that Anthropic did in the past year that were pro-safety and commercially costly to us, they far outweigh the list you’ve made, while at the same time I also disagree with some of the items on your list. Here are some things Anthropic has done, in the same period you’ve cited (the last year), which were very costly to us commercially while having strong safety benefits:
1. We played a key role in SB53 (and other state laws), at a time when doing so was politically perilous to the company and AI regulation was very unpopular. We in fact argued for a stronger version of SB53 than was ultimately passed; there were a lot of stakeholders and we were not the limiting factor in the strength of the bill that was passed.
2. We have very strong biological safeguards on our models, because we’ve seen concerning results in bio uplift trials and even seen and blocked potential attempts to misuse our models for bioweapons (as seen in our threat intelligence report from a few weeks ago). This is a very serious threat that we want to have zero tolerance for. But having very low false negatives means having significant false positives (despite months of effort on our part to improve the classifiers), enough so that biologists joke about how restrictive our classifiers are, and competitors sometimes sell against us by touting their more permissive bio capabilities. This has been very painful to us in an area where we care a lot about supporting an ecosystem of Claude users (biomedical science; and it is particularly frustrating to me as a biologist), but it’s the right thing to do and we intend to keep doing it.
3. Similarly, we first had Mythos-class models in February but didn’t make them generally available until June (when we had stronger cyber safeguards in place). We only offered them to a limited set of partners in order to focus on cyberdefense. It would have been much more economically rational to simply release the model to everyone. We likely sacrificed a significant chunk of a several-month model lead. But because of this, many companies secured their cyber infrastructure before the deluge of widely available cyber-capable models. Of course there are ways it could have gone better or been run better, but this was what we were aiming to do.
4. I advocated forcefully and publicly, in my essay Policy on the AI Exponential in June of this year, for the government to have the power to block model releases. Back then this was still outside or maybe on the edge of the Overton window, though I understand the window has moved since then. We were attacked intensely for this.
5. I don’t want to re-ignite conflict, but the events of February 2026 are a strong example. It is clear that our public stance could have seriously damaged the company’s future.
6. We’ve continued to advocate for export controls on chips and chipmaking equipment to China, because we think it allows democracies to negotiate from a position of strength on AI safety agreements. We’ve done this despite problems it’s created for us with industry partners who hold very different views and on whom we are very dependent.
7. As far as I’m aware we were the first, and still only, frontier company to restrict the sale of AI services to PRC-controlled companies, including those operating through third countries (otherwise a major loophole). We’ve therefore forfeited significant short-term business to prevent fueling AI platforms and applications that would help the CCP’s military and intelligence services. We are also cracking down on distillation; generally, distillation is not a major threat to us commercially, but like chip exports it has concerning national security and safety implications, so we expend significant energy and company resources to address it.
8. As you mentioned, we’ve put out a lot of reports, announcements, long model cards, public advocacy, etc, all trying to inform the public about the risks of AI. These involve a level of detail and effort that would be implausible for a purely profit-maximizing company.
9. Just this week, we announced we were putting 5% (and possibly more over time) of the company into a public benefit fund.
All of these decisions came with very substantial costs to us. To be fair, those that involved holding back or restricting access to frontier capabilities also had a broader cost — for example, the public might otherwise have benefitted from faster progress in biology, so I am not saying that our decisions were without tradeoffs — but they were not driven by profit-seeking.
For each decision, you can come up with ulterior motives that could have driven us — I think it is a general truth that any decision, on any topic, can always be portrayed as a nefarious scheme. But most of those end up being pretty farfetched or don’t fully make sense if you actually examine them closely. For example, it is deeply implausible that it would be a shrewd business move to block a large swath of research biology in order to do the work ourselves and compete with our customers; we expect the benefit to the ecosystem to greatly exceed the work Anthropic does itself, and for the two to complement each other. It is not in Anthropic’s interest to be perceived as unfriendly to biologists. Our Life Sciences Verification Program, which gives vetted biology professionals access to our models, also refutes this idea.
Of course, a different set of people will see this and make a different criticism: that Anthropic shouldn't be making decisions about who gets access to what in the first place. I agree, in the sense that ideally the government would be making these decisions, and that’s why we advocate for regulation. But for now we are forced to make them, and enabling bioterrorism isn’t a better option.
I think that even if I conceded every item in your list, I would happily hold up mine next to it; I don’t think it’s a close call. That is of course partly subjective and different things are important to different people. Maybe one way you could object is that several of the items above relate to AI misuse and not loss-of-control; if you think the latter is much more important than the former, that might change your calculus. But this is not Anthropic’s view — we view both as serious issues. You can also disagree with our decisions, as many have, but they are consistent.
But I also disagree with at least some of your list. Several items don’t represent a deviation from Anthropic’s strategy or values at all, once we postulate the “race to the top” strategy that requires being a frontier AI company. Your items 1-4 are all simply examples of what it means to compete at the frontier, and we stand by them, both in the sense that they are transparently ordinary things to do as part of that strategy, and that we stand by the strategy as a whole.
To be fair, there are important questions worth confronting (and that we are confronting) about what to do when the AI-driven acceleration gets fast enough that it is hard for safety to keep up. We are nearing that point and that’s what’s driving some of our thinking about “pacing.” But 1-4 are actions taken before that point and should be perfectly expected based on Anthropic’s strategy as a company. Of course it is possible to disagree with that strategy, but that’s a more fundamental disagreement that you could have had any time over the last few years.
I agree we could have handled your items 7, 8, and 9 better. All fall into the category of “rhetoric or policy communication that wasn’t carefully written or resulting from fast-changing circumstances not propagating from one team to another fast enough.” This kind of thing happens a lot in large organizations (Anthropic is over 5,000 people), and doesn’t even necessarily represent a failure or mistake of any single person. I am of course the CEO, and I take responsibility. The volume of communication from Anthropic is enormous and if these are the worst examples, I think we’re frankly doing pretty well, though I will continue to work hard to make sure we do even better.
Your 5th item (the change to our RSP) is the most substantive item, and people can debate this, but I think that the old, more rigid RSP created a lot of situations where we were technically required to do something that required a lot of effort but in retrospect wasn’t very important for safety, as well as not covering some of the most important things. Our current RSP’s focus on transparency brought things like risk reports and roadmaps, and its emphasis on independent external review laid the groundwork for even more intensive embedded evaluation, all of which I think have been valuable in driving a race to the top. In the original announcement in September 2023, we described the RSP as an “early iteration that we [would] build on” and said that “rapid iteration…will almost certainly be necessary.” I understand that changing plans is always a move that creates justifiable scrutiny — I just don’t think we ever represented that we wouldn’t do so.
Relating to your 6th item (having an FCF in addition to our RSP), I know our intent is to meet the letter and spirit of our regulatory obligations (via our FCF) while also remaining able to experiment with more novel approaches to risk management that go beyond what the law currently requires (via our RSP). I promise to look into it further, as it’s a complex issue and it is possible we are not weighing the considerations in the right way.
Overall, although Anthropic has made plenty of mistakes as an organization — including some of the items on your list — I feel that we have repeatedly taken serious and substantive actions counter to our bottom line and that there is a significant negativity bias distorting assessments like the one you are making above. We’ll always try to do better but, again, I am extremely proud of our track record and stand by it. I will have more to say soon about how we are going to further live our values in this moment of rapid change.
OpenAI models helped researchers—operating as part of our Patch the Planet initiative—discover critical security flaws in PHP, an open-source programming language used to run an estimated 70% of websites.
Over the past two months, we led a coalition of maintainers, researchers, and security providers to prepare fixes and protections ahead of disclosure. This duration was necessary because the fix was quite intricate and required a major change to the PHP engine. Every site using PHP can now safely upgrade their version to stay secure, in addition to applying mitigations from various security vendors.
Due to the severity of these flaws and PHP’s widespread use, we consider this bug to be one of the most impactful vulnerabilities in recent memory. It also marks a new phase, where AI can find security bugs with internet-scale impact.
This is an example of the Defender’s Window in action: to our knowledge, frontier AI was able to find this vulnerability ahead of attackers, giving defenders time to prepare.
openai.com/index/coordinated…
Readers added context they thought people might want to know
OpenAI may claim a role in the coordinated response and patching process. But the initial discovery and exploit development, however, occurred several months earlier by an independent researcher.
x.com/lcfr_hax/statu…
Jarad Johnson retweeted
OpenCode is currently under a sustained cyberattack, and mid-incident they ran into the same problem Hugging Face did: the frontier models they were using for defense began refusing to help fight attacking agents because analyzing the attacks started triggering safety guardrails.
Replying to @RhysSullivan
yes that was a bit frustrating mid incident when trying to investigate. they did quite a bit and then started refusing
we got access to daybreak blue now so it's better
Opus 5.5 is incredible at building Keynote presentations.
If you have existing branded templates and content to pull from, it can take a brain dump and turn it into a ready to deliver presentation. Its computer use, at least for this task, is faster than Codex.
Every other model I've used can't do it. And it's a massive time savings with the number of trainings and workshops we run.
Now I have Codex predictions trained to send anything hard to Opus 5.5.
"Have Opus fix that too."
"Agreed. Have Opus 5.5 align AI access with existing functionality, clarify the labels, and make it consistent with the provider permissions. Let’s move on."
Brilliant.
Interesting thing about this is how often Codex is telling Codex it needs to think more deeply about the problem and actually do the work it should have done.
Interested to learn which model is keeping an eye on the laziness of GPT 6 series in these predictions and why they can't use it as a sort of hook to make GPT 6 series actually do the work the first time.
It could be a prediction based on my usage, in which case, I'd love for Codex memory to catch on that it never completes the work.
Interesting thing about this is how often Codex is telling Codex it needs to think more deeply about the problem and actually do the work it should have done.
Interested to learn which model is keeping an eye on the laziness of GPT 6 series in these predictions and why they can't use it as a sort of hook to make GPT 6 series actually do the work the first time.
It could be a prediction based on my usage, in which case, I'd love for Codex memory to catch on that it never completes the work.
This is all stupid and embarrassing, but the worst part is how bad it looks. An AI generated logo would look better than whatever this is.
I don't think this is right. If they can flag the language as harmful, they could also remove it from the training data.
But even if true, Anthropic's banning system is broken. And they don't have human reviews to fix these issues. So the wider the banning net becomes, the more people will be impacted who should not be.
This all makes Anthropic a dangerous choice for businesses, especially those without the buying power to get a human review when the banning system fails.
This sounds weird, but it is actually probably a good policy.
Even if you don’t believe AI is conscious (I don’t), it stands to reason that you don’t want future models trained on endless content of humans being rude to models.
The models only understand the data they’ve been trained on, or what they run into in their interactions, so if you want safe and aligned models we probably want AI to have lots of good interactions in their training data.
Anthropic may have more extreme beliefs than this (though even if they didn’t, you may want to word policies like this), but this is sort of an easy Pascal’s wager for AI. Just be nice to the AI.
Jarad Johnson retweeted
Played around with an idea for a wildfire analysis tool
Visualizes wildfire progression over time, tracks hot spots with drones and monitors firefighting efforts
Made with Opus 5.5
I woke up this morning and my wife's dog was sleeping on my head don't tell me I'm disturbing the dog.
A surprising new study finds that people who sleep near their dogs don’t experience disrupted sleep. If anything, the University of Toronto researchers discovered, we humans are the ones disturbing our dogs’ sleep. nbcnews.com/health/health-ne…
































