Kalakshar US

Algoriddim’s djay Pro software has always had close ties to Apple and often been at the forefront of new DJ tech, especially on Mac, iOS or iPadOS. Today marks the launch of djay Pro version 5 and it includes a variety of novel features, many of which leverage the company’s AI and a new partnership with the interactive team at AudioShake.

There are several buzzy trademarked names to remember this time around including Next-generation Neural Mix, Crossfader Fusion and Fluid Beatgrid. These are the major points of interest in djay Pro 5, with only a passing mention of improved stem separation on mobile, UI refreshes for the library and a new simplified Starter Mode that may cater to new users on the platform. The updates include some intriguing AI-automated features that put the system in control of more complex maneuvers. Best of all, existing users get it all for free as part of their subscription.

AudioShake and Algroiddim have been working on their audio separation tech (like many other companies) and are calling this refreshed version Next-generation Neural Mix. We’re told to expect crisp, clear separation of elements from vocals, harmonies and drums. The tools have also been optimized for mobile devices, as long as they run a supported OS.

Fluid Beatbrid is perhaps one of the easiest to understand and seems to be an underlying part of the crossfader updates. Anyone who’s used beatgrids knows they’re rarely perfect on first analysis and often take a bit of work to lock in, especially on tracks that need it. Songs with live instrumentation that tend to shift tempo naturally, EDM with varying tempo shifts during breakdowns and even just older dance tracks that tend to meander slightly throughout playback have been pain points. Fluid Beatgrid is supposed to use AI to accommodate for those shifts and find the right points to mark.

Crossfader Fusion is where stems, automation and those beatgrids all come into play. There are now a variety of settings for the crossfader beyond the usual curves. One of the highlighted modes is the Neural Mix (Harmonic Sustain) setting. This utilizes stem separation and automated level adjustments as you go from one track to the next.

For those who enjoy cutting and scratching, there are crossfade settings that use automated curves and spatial effects so, for example, outgoing track vocals can be dropping out as you cut into the next track automatically. The incoming track’s vocals can be highlighted for scratching and as your mix completes the transition, things are blended together further with AI.

There’s even an example provided that shows how you can mix across vastly different BPMs, where the incoming song matches up with a slower outgoing track, but its original tempo is slowly integrated during the transition leaving you with the new faster tempo. 

Existing users should be alerted to the update, but newcomers can find djay Pro version 5 starting today at the App Store. While there will continue to be a free version, the optional Pro subscription costs $7 per month or $50 per year and gives you access to all the features across Mac, iOS and iPhone. Support for the app includes devices running MacOS 10.15 or later and iOS 15 / iPadOS 15 or later.

And as a side note, we’re told that djay Pro for Windows users were leveled up in September and will get Fluid Beatgrid in an update for that platform as soon as next week. Newer features like Crossfader Fusion are expected in the near future.

This article originally appeared on Engadget at https://www.engadget.com/ai-joins-you-in-the-dj-booth-with-algoriddims-djay-pro-5-150007224.html?src=rss 

Undoubtedly, 2023 has been the year of generative AI, and Google is marking its end with even more AI developments. The company has announced the creation of its most powerful TPU (formally known as Tensor Processing Units) yet, Cloud TPU v5p, and an AI Hypercomputer from Google Cloud. “The growth in [generative] AI models — with a tenfold increase in parameters annually over the past five years — brings heightened requirements for training, tuning, and inference,” Amin Vahdat, Google’s Engineering Fellow and Vice President for the Machine Leaning, Systems, and Cloud AI team, said in a release.

The Cloud TPU v5p is an AI accelerator, training and serving models. Google designed Cloud TPUs to work with models that are large, have long training periods, are mostly made of matrix computations and have no custom operations inside its main training loop, such as TensorFlow or JAX. Each TPU v5p pod brings 8,960 chips when using Google’s highest-bandwidth inter-chip interconnect.

The Cloud TPU v5p follows previous iterations like the v5e and v4. According to Google, the TPU v5p has two times greater FLOPs and is four times more scalable when considering FLOPS per pod than the TPU v4. It can also train LLM models 2.8 times faster and embed dense models 1.9 times faster than the TPU v4. 

Then there’s the new AI Hypercomputer, which includes an integrated system with open software, performance-optimized hardware, machine learning frameworks, and flexible consumption models. The idea is that this amalgamation will improve productivity and efficiency compared to if each piece was looked at separately. The AI Hypercomputer’s performance-optimized hardware utilizes Google’s Jupiter data center network technology.

In a change of pace, Google provides open software to developers with “extensive support” for machine learning frameworks such as JAX, PyTorch and TensorFlow. This announcement comes on the heels of Meta and IBM’s launch of the AI Alliance, which prioritizes open sourcing (and Google is notably not involved in). The AI Hypercomputer also introduces two models, Flex Start Mode and Calendar Mode. 

Google shared the news alongside the introduction of Gemini, a new AI model that the company calls its “largest and most capable,” and its rollout to Bard and the Pixel 8 Pro. It will come in three sizes: Gemini Pro, Gemini Ultra and Gemini Nano. 

This article originally appeared on Engadget at https://www.engadget.com/google-announces-new-ai-processing-chips-and-a-cloud-hypercomputer-150031454.html?src=rss 

OpenAI’s spot atop the generative AI heap may be coming to an end as Google officially introduced its most capable large language model to date on Wednesday, dubbed Gemini 1.0. It’s the first of “a new generation of AI models, inspired by the way people understand and interact with the world,” CEO Sundar Pichai wrote in a Google blog post.

“Ever since programming AI for computer games as a teenager, and throughout my years as a neuroscience researcher trying to understand the workings of the brain, I’ve always believed that if we could build smarter machines, we could harness them to benefit humanity in incredible ways,” Pichai continued.

The result of extensive collaboration between Google’s DeepMind and Research divisions, Gemini has all the bells and whistles cutting-edge genAIs have to offer. “Its capabilities are state-of-the-art in nearly every domain,” Pichai declared. 

The system has been developed from the ground up as an integrated multimodal AI. Many foundational models can be essentially though of groups of smaller models all stacked in a trench coat, with each individual model trained to perform its specific function as a part of the larger whole. That’s all well and good for shallow functions like describing images but not so much for complex reasoning tasks.

Google, conversely, pre-trained and fine-tuned Gemini, “from the start on different modalities” allowing it to “seamlessly understand and reason about all kinds of inputs from the ground up, far better than existing multimodal models,” Pichai said. Being able to take in all these forms of data at once should help Gemini provide better responses on more challenging subjects, like physics.

Gemini can code as well. It’s reportedly proficient in popular programming languages including Python, Java, C++ and Go. Google has even leveraged a specialized version of Gemini to create AlphaCode 2, a successor to last year’s competition-winning generativeAI. According to the company, AlphaCode 2 solved twice as many challenge questions as its predecessor did, which would put its performance above an estimated 85 percent of the previous competition’s participants.

While Google did not immediately share the number of parameters that Gemini can utilize, the company did tout the model’s operational flexibility and ability to work in form factors from large data centers to local mobile devices. To accomplish this transformational feat, Gemini is being made available in three sizes: Nano, Pro and Ultra. 

Nano, unsurprisingly, is the smallest of the trio and designed primarily for on-device tasks. Pro is the next step up, a more versatile offering than Nano, and will soon be getting integrated into many of Google’s existing products, including Bard.

Starting Wednesday, Bard will begin using a especially-tuned version of Pro that Google promises will offer “more advanced reasoning, planning, understanding and more.” The improved Bard chatbot will be available in the same 170 countries and territories that regular Bard currently is, and the company reportedly plans to expand the new version’s availability as we move through 2024. Next year, with the arrival of Gemini Ultra, Google will also introduce Bard Advanced, an even beefier AI with added features.

Pro’s capabilities will also be accessible via API calls through Google AI Studio or Google Cloud Vertex AI. Search (specifically SGE), Ads, Chrome and Duet AI will also see Gemini functionality integrated into their features in the coming months.

Gemini Ultra won’t be available until at least 2024, as it reportedly requires additional red-team testing before being cleared for release to “select customers, developers, partners and safety and responsibility experts” for testing and feedback.” But when it does arrive, Ultra promises to be an incredibly powerful for further AI development.

This article originally appeared on Engadget at https://www.engadget.com/googles-answer-to-gpt-4-is-gemini-the-most-capable-model-weve-ever-built-150039571.html?src=rss 

Half of London’s black cab fleet is now made up of zero-emission vehicles, manufacturer LEVC and Transport for London (TfL) announced. Of the 14,690 licensed taxis in the capital, 7,972 are battery electric vehicles (BEVs), with most manufactured by Geely’s LEVC, according to the latest figures. The number of those models grew a fairly dramatic 10 percent in the last month alone. 

“Reaching this milestone is a great reflection of how London is working hard to be a greener, more sustainable, environmentally friendly city,” said TfL’s Helen Chapman. “London’s black taxis are recognized worldwide and we are proud to see that so many drivers are helping clean up the air.” 

New drivers haven’t had a choice in the matter, though, as since 2018, TfL has required that all new cabs licensed in the city be zero emissions cable (the rule was extended to private minicabs last year). Cabbies with existing licenses have been motivated to change, too, as any still using less efficient vehicles have been required since 2020 to pay a daily rate (now £12.50) to operate in central London’s Ultra Low Emission Zone.

Many of London’s larger taxi and minicab operators have committed to fully-electric fleets by 2025. That includes the city’s largest operator, Addison Lee (which uses VW ID 4s) saying it would reach that goal by 2023. London’s Black Cabs are generally independently owned and licensed under strict rules by TfL. Uber recently announced that London’s black taxis would be listed on its app and while some drivers have signed up, many decried the plan. 

This article originally appeared on Engadget at https://www.engadget.com/half-of-londons-famed-black-cab-taxi-fleet-are-now-evs-134015907.html?src=rss