When you flip the Lick around, things look more complicated—especially if you’re new to suction play—but if you take your time to understand these features, you’ll be a happy camper. On this end, you have a suction cup and a tongue-shaped clitoral stimulator. Remove the cup—just a quick twist and it’s off—you can easily access the flicking tongue. The tongue has three speeds that, with a bit of water-based lube, are meant to mimic the sensation of oral sex.

It didn’t feel much like oral sex to me, which probably says more about my partners than the Lick, but it felt great against my clitoris. So much so that this was my favorite function of the Lick. However, I want to stress the importance of lube. To truly experience the incredible sensations, you want it to glide seamlessly over your clitoris. Because your clit doesn’t naturally lubricate, the best way to make that happen is with your favorite water-based lube.

Finally, we get to the suction feature. While not as intense as sex toys that market themselves as bona fide pussy pumps, the suction on the Lick is pretty strong. Before I used it on my vulva, I used the pump of my hand to get an idea of what I was up against, and there was some major sucking happening. If you’re unsure why this might be an asset when dealing with pleasure, it comes down to sensitivity.

With the suction cup on your vulva, each time you press the corresponding button, it tightens its grip, essentially demanding that more blood come into the vulva. When this happens, sensitivity in the area is heightened, which, for some, can lead to stronger and longer orgasms. While not a sensation that everyone may be into, it is one that, if you haven’t tried it, is worth giving it a whirl at least once—if only to prove to yourself it’s not (or absolutely is) for you.

Some Initial Finagling

As much as the Lick’s features deliver on the pleasure front, the four control buttons are a bit difficult to navigate at first. When you hold the Lick in your hand with the suction cup at the top, the buttons descend in order down the shaft. The on/off button is second-to-last—most sex toys give this button its own spot, or at the top or bottom of the layout of buttons. That way, you won’t push it accidentally in the heat of the moment and kill the vibe. Sadly, that exact thing happened to me. The buttons just didn’t make sense in my brain.

Battery life is very much dependent on how you use the Lick. It takes about two hours to fully charge, and with that, you can get anywhere from 80 to 180 minutes of run time. I didn’t exhaust the vibrator by trying to get 180 minutes out of it, but that’s a broad spectrum of time that should be taken into consideration.

Ultimately, the Le Wand Lick 3-in-1 does exactly what it promises: gets you off. It’s waterproof, has a unique look, and its trio of options keeps things interesting. I’ve only used the Lick solo, but I can definitely see the pussy pump feature being a fun little addition to partnered play.

As the internet of things (IoT) evolves and expands, among the most recent developments is the integration of artificial intelligence (AI) capabilities directly onto IoT devices to unlock a new generation of applications. Now, a study from IoT analysts at Berg Insight has found that the on-device AI market having risen by 22% from 2023-2024.

Over the course of the lpst few years, leading technology providers have demonstrated how on-device AI is driving a number of use cases – in particular, automotive and industry 4.0 applications – with embedded AI platforms, as well as micro-power Wi-Fi silicon on chip (SoC), enabling intelligent computing.

In its study, The on-device AI market for IoT applications, Berg Insight said that it has identified 40 key companies that shape the on-device AI landscape, and it believes that the market can broadly be divided into two layers. The first encompasses hardware categories such as AI SoCs or system-on-modules (SoMs), AI accelerators and AI microcontroller units (MCUs), each optimised for different levels of performance, power efficiency and integration.

The analyst said AI SoCs typically integrate components such as general-purpose and specialised AI compute cores, on-chip memory and connectivity on a single chip, while SoMs extend this design by including external system memory, storage and interface components on a larger board, targeting more advanced use cases. AI accelerators are those designed to enhance AI inference efficiency in existing systems, typically working alongside a separate host processor in embedded applications.

AI MCUs serve lower-power devices by bringing neural network capabilities to sensors, wearables and IoT endpoints where energy efficiency and cost are most critical. The second layer consists of on-device AI platforms that combine hardware, software and developer tools to simplify model deployment and optimisation.

In all, Berg calculates that the on-device AI market reached US$ 10.1bn 2024 in a market including AI SoCs/SoMs, AI accelerators, AI MCUs and specialised on-device AI software and platforms. The analyst expects the market to grow to US$ 30.6bn in 2029, representing a compound annual growth rate (CAGR) of 25%. The figures excluded revenues generated by non-IoT applications such as smartphones, tablets and personal computers.

Berg noted that the market for on-device AI solutions is characterised by a high degree of heterogeneity in both technologies and applications, in contrast to cloud-based AI where the hardware is typically designed around predefined use cases and centralised infrastructure. It added that embedded AI processing can be architected in numerous ways depending on the end use case, and it can be integrated into an almost limitless range of devices across consumer, industrial and automotive domains.

The analyst said this leads to a differentiated market landscape, with unique design constraints, performance requirements and optimisation strategies. However, it cautioned that the overarching objective is typically the same for all suppliers, which is to achieve the highest possible performance per watt for the intended use case.

“Over the past decade, the on-device AI market has been driven primarily by traditional machine learning use cases such as computer vision and anomaly detection, which have seen steady annual growth of around the 10 percent range,” said Berg Insight IoT analyst Melvin Sorum.

“In recent years, the market has reached an inflexion point as emerging technologies and applications in generative AI, robotics and autonomous driving have opened up new dimensions of growth. These developments are expected to accelerate market growth and give rise to entirely new use cases and product categories.”

Just a year after NTT Docomo concluded a test with radio waves in the 4.8GHz wireless band, which found that indoor 6G communication speeds can be improved up to 18% compared with conventional methods, the firm has “successfully conducted the world’s first” outdoor demonstration using real-time transceiver systems with AI-powered wireless technology for 6G.

The operator has already been at the forefront of a string of developments moving towards the era of 6G, and the latest move saw NTT work with Nokia Bell Labs and SK Telecom in field trials taking place at three locations in the city of Yokosuka in Kanagawa prefecture.

NTT said that in wireless communications, fluctuations in the radio propagation environment can cause unstable connection quality. To address this issue, the three parties have been developing and testing “AI-AI technology”, which applies artificial intelligence to both the transmitting and receiving sides of the wireless interface to optimise modulation and demodulation schemes according to radio conditions, enabling stable communication across diverse use cases.

The effectiveness of this technology is said to have been proved in the indoor tests undertaken a year ago.

The latest field trials aimed to verify whether this new technology can maintain stable performance in outdoor environments, where radio conditions vary greatly due to temperature, weather and obstacles. The trials are said to have confirmed that the use of AI improved throughput (transmission speed) by up to 100% compared with conventional non-AI-based methods under the same environmental conditions, effectively doubling the communication speed.

In the field trials, Docomo and partners evaluated the AI-AI technology under three outdoor environments with varying radio propagation conditions, such as the presence of obstacles and whether the terminal was stationary or in motion. Namely Course 1, which consisted of a public road with gentle curves where the test vehicle travelled at speeds of up to 40 km/h; Course 2, an environment with partial obstacles; and Course 3, a road with few obstacles where the test vehicle travelled at speeds of up to 60 km/h.

The evaluations were conducted using devices equipped with the technology to compare throughput performance with and without its application.The results were claimed to have confirmed that applying the AI-AI technology improved communication speed by compensating for signal degradation across all test environments.

In particular, NTT noted that under the most complex propagation conditions in Course 1, the technology achieved an average throughput improvement of 18% and a maximum of 100% compared with conventional methods. This improvement it stressed would enable users to transmit larger volumes of data at higher speeds, while also allowing network operators to enhance spectrum efficiency and deliver higher-quality communication services.

Docomo also believes that the findings demonstrated that the AI-AI technology is effective not only indoors but also in complex outdoor environments, marking a significant step toward practical 6G systems that combine high wireless transmission efficiency with low power consumption.

The company said that it will continue to refine the new technology under diverse conditions and accelerate R&D toward 6G realisation, while also collaborating with global partners to advance 6G standardisation and implementation.