LG's best OLED TV of 2024 is on sale for $1,000 off today

We here at Digital Trends have loved the last few LG OLED TVs. Just last year, our editorial team praised the LG G4 Series 4K OLED, saying, 'The LG G4 is a triumph of modern television engineering.' As luck would have it, the 65-inch size of this TV is actually on sale this week:
For a limited time, the LG 65-inch G4 Series 4K OLED is discounted to $2,400 at retailers like Amazon and Best Buy or directly through the manufacturer. In fact, if you buy through LG, you'll also qualify for a free wall-mounting service (and a $70 wall mount) or furniture assembly.
Why you should buy the LG G4 Series
There really isn't anything the LG G4 Series can't do. It delivers phenomenal colors and near-perfect contrast levels. Thanks to the TV's self-emissive pixel tech, you can expect inky blacks and top-shelf picture accuracy. And unlike some of the other best OLED TVs out there, the LG G4 also gets bright enough when watching SDR content to comfortably place it in a well-lit room.
The OLED display does a nice job at combating glare and reflections, too, though we wouldn't recommend placing a floor lamp anywhere near the screen. While the LG G4 doesn't support HDR10+, the TV is compatible with every other HDR format, which means you'll be treated to glorious highlights and enhanced colors when watching a Dolby Vision, HDR10, or HLG-encoded film.
As far as motion clarity goes, the G4 boasts a native 144Hz refresh rate, as well as HDMI 2.1 connectivity and VRR and ALLM support. This makes it one of the best TVs for gaming in 2025.
Apps, screen mirroring, and other Internet-powered features are provided through LG's webOS 24 software. Stream Netflix and YouTube, watch hundreds of free live TV stations, and more!
It's hard to say how long this markdown and LG promo is going to last, but now that the LG G5 Series is hitting shelves, we expect the LG G4 to be discounted more often. We also recommend taking a look at our lists of the best LG TV deals, best OLED TV deals, and best TV deals for even more sales on top LG products!

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Tesla Misses Robotaxi Launch Date, Goes With Safety Drivers

A vehicle Tesla is using for robotaxi testing purposes in Austin, Texas, US, on Friday, June 20, ... More 2025.. Photographer: Eli Hartman/Bloomberg Tesla's much-anticipated June 22 'no one in the vehicle' Robotaxi launch in Austin is not ready. Instead, Tesla has announced to its invite-only passengers that it will operate a limited service with Tesla employees on board the vehicle to maintain safety. Tesla will use an approach that was used in 2019 by Russian robotaxi company Yandex, putting the safety driver in the passengers seat rather than the driver's seat. (Yandex's robotaxi was divested from Russian and now is called AVRide.) Having an employee on board, commonly called a safety driver, is the approach that every robocar company has used for testing, including testing of passenger operations. Most companies spend many years (Waymo spent a decade) testing with safety drivers, and once they are ready to take passengers, there are typically some number of years testing in that mode, though the path to removing the safety driver depends primarily on evaluation of the safety case for the vehicle, and less on the presence of passengers. Tesla has put on some other restrictions--rides will be limited to 6am to midnight (the opposite of Cruise's first operations, which were only at night) and riders come from an invite-only list (as was also the case for Waymo, and Cruise and others in their early days.) Rides will be limited to a restricted service area (often mistakenly called a 'geofence') which avoids complex and difficult streets and intersections. Rides will be unavailable in inclement weather, which also can happen with other vehicles, though fairly rarely today. Tesla FSD is known to disable itself if rain obscures some of its cameras--only the front cameras have a rain wiper. The fleet will be small. Waymo started testing with safety drivers in 2009, gave rides to passengers with safety drivers in 2017, and without safety drivers in 2020 in the Phoenix area. Cruise had a much shorter period with passengers and safety drivers. Motional has given rides for years but has never removed the safety driver. Most Chinese companies spent a few years doing it. Giving passengers rides requires good confidence in the safety of the system+safety driver combination, but taking the passengers does not alter how well the vehicle drives, except perhaps around pick-up and drop-off. (While a vehicle is more at liberty to make hard stops with no passengers on board, I am aware of no vehicle which takes advantage of this.) As such we have no information on whether Tesla will need their safety drivers for a month or a several years, or even forever with current hardware. Passenger's Seat vs. Driver's Seat Almost all vehicles use a safety driver behind the wheel. Tesla's will be in the passenger seat, in a situation similar to that used by driving instructors for student human drivers. While unconfirmed by Tesla, the employee in the passenger seat can grab the wheel and steer. Because stock Teslas have fully computer controlled brake and acceleration, they might equip the driver with electronic pedals. Some reports have suggested they have a hand controller or other ways to command the vehicle to brake. There is no value to putting the safety driver on the passengers side. It is no safer than being behind the wheel, and believed by most to be less safe because of the unusual geometr20 November 2024, Berlin: A prototype of the Tesla Cybercab stands in a showroom in the Mall of Berlin. Photo: Hannes P. Albert/dpa (Photo by Hannes P Albert/picture alliance via Getty Images)y. It's hard to come up with any reason other than just how it looks. Tesla can state the vehicles have 'nobody in the driver's seat' in order to attempt to impress the public. The driving school system works, so it's not overtly dangerous, but in that case there's an obvious reason for it that's not optics. Tesla Cybercab concept. With only 2 seats and no controls, not very suitable for a safety driver. ... More These are not being used in Tesla's Austin pilot. That said, most robocar prototypes, including Tesla supervised FSD, are reasonably safe with capable safety drivers. A negligent and poorly managed safety driver in an Uber ATG test vehicle killed a pedestrian in Tempe, Arizona when the safety driver completely ignored her job, but otherwise these systems have a good record. The combination of Tesla Autopilot and a supervising driver has a reasonable record. (The record is not nearly as good as some people think Tesla claims. Every quarter, Tesla publishes a deeply misleading report comparing the combination of Tesla Autopilot plus supervisor to the general crash rate, but they report airbag deployments for the Teslas mostly on freeways and compare it without general crash numbers on all roads for general drivers. This makes it seem Autopilot is many times safer than regular drivers when it's actually similar, a serious and deceitful misrepresentation.) As noted, Yandex, now AVRide, has used safety drivers in the passenger seat, and has done so in Austin--also speculated to be mostly for optics, though there are some legal jurisdictions where companies shave made this move because the law requires safety drivers and they hope to convey an aura of not needing them. This has also been the case in China.) When Cruise did their first 'driverless' demo ride in San Francisco, they had an employee in the passengers seat. So Tesla has been ready to run with safety drivers for years. What's tested here isn't the safety of the cars, but all the complexity of handling passengers, including the surprising problems of good PuDo (Pick-up/Drop-off.) Whether Teslas can operate a safe robotaxi with nobody onboard, particularly with their much more limited sensor hardware, remains to be seen. Other Paths To Launch Tesla apparently experimented with different paths to getting out on the road before they are ready to run unsupervised. In particular, vehicles were seen with the passenger seat safety driver, and also being followed by a 'chase car' with two on board. Reports also came of Tesla planning for 'lots of tele-ops' including not just remote assistance (as all services do) but remote supervision including remote driving. We may speculate that Tesla evaluated many different approaches: Because Elon Musk promised 'nobody in the car' and 'unsupervised' in the most recent Tesla earnings call, there was great pressure to produce #1, but the Tesla team must have concluded they could not do that yet, and made the right choice, though #3 is a better choice than #4. They also did not feel up to #2, which is commonly speculated to be what other companies have done on their first launch, later graduating to #1 #5 just looks goofy, I think the optics would not work, and it's also challenging. Remote driving is real and doable--in spite of the latency and connectivity issues of modern data networks--but perhap Tesla could not get it ready in time. All teams use remote assistance operators who do not drive the cars, but can give them advice when they get confused by a situation, and stop and ask for advice. Even Waymo recently added a minor remote driving ability for low-speed 'get the car out off the road' sort of operations. I have recommended this for some time. It is worth noting the contrast beween Cruise's 'night only' launch and Tesla's mostly-daytime one. Cruise selected the night because there is less traffic and complexity. LIDARs see very well at night. Tesla's camera-based system has very different constraints at night and many fear it's inferior then. On the other hand Tesla will operate in some night hours and with more cars and pedestrians on the street. The question for Tesla will be whether the use of safety drivers is a very temporary thing, done just because they weren't quite ready but needed to meet the announced date, or a multi-year program as it has been for most teams. Tesla is famous for not meeting the forecast ship dates for its FSD system, so it's not shocking that this pattern continues. The bigger question is whether they can do it at all. Tesla FSD 13, the version available to Tesla owners, isn't even remotely close to robotaxi ready. If Tesla has made a version which is closer, through extra work, training and severe limitations of the problem space, it's still a big accomplishment. This will be seen in the coming months. Two robocar teams had severe interactions with pedestrians. Both those teams, and one pedestrian, are dead. Tesla knows they must not make mistakes.

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23 minutes ago

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Using AI in Customer Service? Don't Make These 4 Mistakes

AI is revolutionizing customer service in 2025, offering speed, personalization and efficiency. But to avoid frustrating users, businesses must ensure the following things. Opinions expressed by Entrepreneur contributors are their own. AI is omnipresent in 2025 in all areas of the business sphere, including customer service. And for good reason. Used right, AI can provide invaluable insights into your customers' behaviors and preferences, boost the efficiency of your customer service team and increase overall satisfaction. Between dynamic personalization, streamlined purchase processes and predictive customer support, many small businesses are leveraging AI to level the playing field and provide enterprise-grade customer service. However, despite AI's massive potential, there are several potential pitfalls when using AI in customer service. At worst, AI can scare off customers or generate frustration, rather than helping to streamline processes. Here are the four most common mistakes — and how to avoid them. Related: How Small Businesses Can Leverage AI Without Breaking the Bank 1. Frustrating generic chatbots To start with, chatbots can be a great asset to your team members and customers alike. They can speedily handle routine queries, free up your agents' capacities, respond to customers even outside regular business hours and reduce wait times. However, to be effective, chatbots need to be well-trained and personalized. Unfortunately, many companies — in a rush to stay ahead in the AI race — deployed chatbots that ask too many questions, give generic answers and fail to solve queries. In one hilarious example, NYC's MyCity chatbot kept giving wrong answers even six months post-deployment and after $600,000 in investments, misinforming users about legal requirements for business owners and even basic facts such as the minimum wage. Overall, 80% of people reported that interactions with chatbots have increased their frustration rather than leading to quicker solutions to the issues they were facing. To avoid this, it's crucial that chatbots are trained well on company-internal data. Ideally, they should be able to leverage customer-specific data across a number of different channels in order to provide personalized, efficient support to every person who reaches out. 2. Unaccessible siloed data On that note, another common pitfall to avoid when implementing AI in customer service is data siloing. One of AI's greatest strengths is its capacity to process huge amounts of data and unearth patterns and trends, condensed into actionable insights. These insights can then be leveraged for personalization and targeted strategy adjustments. However, that's only possible if AI actually has access to all the necessary data elements — and that is a challenge many small businesses are currently facing. In fact, a recent study by Nextiva, a market leader in customer experience software solutions, found that among company leadership, data siloing was identified as one of the most common barriers to AI implementation. In the study, 39% of respondents agreed that they "struggled with accessibility, aggregation, integration and structure of real-time and historical data." To avoid this limitation, it's essential to audit data storage and integration as soon as you start planning your AI implementation strategy. Making sure from the start that the systems you are considering integrate well — or that bridge solutions are at least available — will avoid unnecessary siloing and frustration down the line. Related: AI Can Give You New Insights About Your Customers for Cheap. Here's How to Make It Work for You. 3. Going overboard on hyper-personalization and automation On the other end of the spectrum are businesses that go overboard in their enthusiasm for AI, to a degree that can appear off-putting to many customers. This includes hyper-personalization and automation processes. While personalization is a key advantage of AI and can boost the efficiency of customer service agents and the satisfaction of the people they interact with, you don't want to appear omniscient either. Having the impression that a company knows everything about them before they even talk to you is seen as acutely creepy by many customers. Salesbots, in particular, often trigger the uncanny valley effect, or scare off potential customers by leveraging information they don't feel they ought to have access to. To steer clear of this particular pitfall, it's essential to carefully calibrate the level of personalisation you implement and weigh its potential benefits in boosting conversions against customers' perception of intrusiveness. 4. Forgetting human escalation options Finally, a widespread mistake small businesses make in leveraging AI for customer service is to neglect human escalation options, especially in customer support. No matter what your AI can do, it's always necessary to offer customers the option to talk to a human agent instead. There is nothing more frustrating for a customer facing an urgent problem than being stuck in an ineffective conversation loop with a chatbot or a virtual phone agent when an actual person would clearly help them reach a solution far more efficiently. Outside business hours, when AI is the only one holding down the fort, it's often enough to offer customers the option to leave a message and assure them you will contact them as soon as possible. Other than that, though, you need to give people the option of a human lifeline to help put out an urgent fire. Related: Does AI Deserve All the Hype? Here's How You Can Actually Use AI in Your Business Conclusion In 2025, AI is an incredible asset that small businesses can leverage to elevate their customer service. It is, however, not a panacea. To effectively harness the potential of AI and avoid common pitfalls, it's necessary to carefully plan and train the systems you're deploying, exercise discretion with respect to personalization and implement a human failsafe option. By sticking to these tenets, though, you'll be able to make the most of the opportunities AI has to offer for small businesses in customer service and increase your overall customer satisfaction.

Yahoo

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Declining Stock and Decent Financials: Is The Market Wrong About Dayforce Inc. (NYSE:DAY)?

Dayforce (NYSE:DAY) has had a rough three months with its share price down 6.0%. But if you pay close attention, you might find that its key financial indicators look quite decent, which could mean that the stock could potentially rise in the long-term given how markets usually reward more resilient long-term fundamentals. Specifically, we decided to study Dayforce's ROE in this article. Return on Equity or ROE is a test of how effectively a company is growing its value and managing investors' money. In short, ROE shows the profit each dollar generates with respect to its shareholder investments. Trump has pledged to "unleash" American oil and gas and these 15 US stocks have developments that are poised to benefit. The formula for return on equity is: Return on Equity = Net Profit (from continuing operations) ÷ Shareholders' Equity So, based on the above formula, the ROE for Dayforce is: 1.0% = US$26m ÷ US$2.6b (Based on the trailing twelve months to March 2025). The 'return' refers to a company's earnings over the last year. Another way to think of that is that for every $1 worth of equity, the company was able to earn $0.01 in profit. View our latest analysis for Dayforce Thus far, we have learned that ROE measures how efficiently a company is generating its profits. Based on how much of its profits the company chooses to reinvest or "retain", we are then able to evaluate a company's future ability to generate profits. Assuming everything else remains unchanged, the higher the ROE and profit retention, the higher the growth rate of a company compared to companies that don't necessarily bear these characteristics. It is quite clear that Dayforce's ROE is rather low. Even compared to the average industry ROE of 20%, the company's ROE is quite dismal. Dayforce was still able to see a decent net income growth of 15% over the past five years. We reckon that there could be other factors at play here. For example, it is possible that the company's management has made some good strategic decisions, or that the company has a low payout ratio. As a next step, we compared Dayforce's net income growth with the industry, and pleasingly, we found that the growth seen by the company is higher than the average industry growth of 11%. Earnings growth is an important metric to consider when valuing a stock. It's important for an investor to know whether the market has priced in the company's expected earnings growth (or decline). Doing so will help them establish if the stock's future looks promising or ominous. Is DAY fairly valued? This infographic on the company's intrinsic value has everything you need to know. Dayforce doesn't pay any regular dividends currently which essentially means that it has been reinvesting all of its profits into the business. This definitely contributes to the decent earnings growth number that we discussed above. In total, it does look like Dayforce has some positive aspects to its business. With a high rate of reinvestment, albeit at a low ROE, the company has managed to see a considerable growth in its earnings. Having said that, looking at the current analyst estimates, we found that the company's earnings are expected to gain momentum. To know more about the latest analysts predictions for the company, check out this visualization of analyst forecasts for the company. Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data