IBM AI Enhances US Open, Announces Telm2
Key Points
- IBM Consulting partnered with the USTA to power the US Open’s digital experience, deploying enterprise‑ready Granite foundation models for large‑scale generative AI content creation.
- The “content engine” used the Granite‑13B chat model to automatically generate pre‑match bullet points, detailed post‑match reports, and spoken commentary/subtitles by pulling from match statistics and player data.
- Improvements to AI‑generated audio commentary focused on making the voice sound natural through tuning of top‑K and temperature sampling parameters, as well as careful pitch and speed adjustments, enabling near‑real‑time, largely unsupervised output.
- IBM announced the next‑generation TELM 2 processor and the upcoming IBM Spire AI accelerator, slated for release in 2025, marking a new era of enterprise computing optimized for AI inferencing.
Full Transcript
# IBM AI Enhances US Open, Announces Telm2 **Source:** [https://www.youtube.com/watch?v=VFEJrddQIb4](https://www.youtube.com/watch?v=VFEJrddQIb4) **Duration:** 00:04:41 ## Summary - IBM Consulting partnered with the USTA to power the US Open’s digital experience, deploying enterprise‑ready Granite foundation models for large‑scale generative AI content creation. - The “content engine” used the Granite‑13B chat model to automatically generate pre‑match bullet points, detailed post‑match reports, and spoken commentary/subtitles by pulling from match statistics and player data. - Improvements to AI‑generated audio commentary focused on making the voice sound natural through tuning of top‑K and temperature sampling parameters, as well as careful pitch and speed adjustments, enabling near‑real‑time, largely unsupervised output. - IBM announced the next‑generation TELM 2 processor and the upcoming IBM Spire AI accelerator, slated for release in 2025, marking a new era of enterprise computing optimized for AI inferencing. ## Sections - [00:00:00](https://www.youtube.com/watch?v=VFEJrddQIb4&t=0s) **IBM AI Powers US Open Coverage** - IBM leveraged its Granite foundation models on Watson X to automatically produce pre‑match bullet points, detailed post‑match reports, and spoken commentary for every US Open singles match. ## Full Transcript
IBM at the US Open and a look at the new
telm 2 processor all on this episode of
IBM Tech
now for more than three decades IBM
Consulting has collaborated with the
United States tennis Association to
provide an engaging digital experience
for US Open tennis fans of course this
year's tournament was no different and
we're going to look at two amazing
generative AI projects that leverage
IBM's versatile family of enterprise
ready Granite Foundation models the
first project was the content engine
which was responsible for providing
up-to-date story coverage for the
hundreds of matches across the men's and
women's singles competition truly a
massive undertaking the content engine
produced three main outputs bullet point
descriptive texts before and after every
singles match multi-paragraph match
reports that provided descriptive
summaries and Analysis about completed
matches and spoken commentary and
subtitles for match highlights the
granite 13B chat model was responsible
for producing our bullet points before
and after each match pre-match bullet
points Drew from Myriad data points and
gave insights based on rankings
head-to-head results and player
biographies when a match was finished
the system generated text descriptions
of what happened drawn from stats such
as Aces break points one double faults
winners and shot speed then the match
reports were created these reports Drew
on trusted Us open data and used the
combined power of granite and other
models hosted on IBM Watson x. to create
long form summaries the second major
project was AI generated spoken
commentary and subtitles for match
highlights introduced last year AI
generated audio commentary provides
automated voiceovers and subtitles for
every singles match highlight reel shown
on the US Open website and app this year
a key goal was to make the audio
commentary more natural and human this
included experimenting with two
variables top K which is a parameter
that controls the number of possible
answers the model should consider and
temperature sampling which was used to
adjust the probability distribution of
possible answers after extensive testing
the next step was going from text to
speech where it was essential to make
the voices sound convincingly human
through experimentation and many
different runs the teams made sure the
voices were clear and had the right proy
in other words the pitch and speed
matched the nature of what was being
said when these balances were found the
inference and output processes happened
largely unsupervised in near real time
to learn more about IBM at the US Open
check out the link in the description of
this
video next up in 2021 IBM introduced the
IBM telm processor featuring its first
Advanced on-processor chip AI
accelerator for inferencing now we're
excited to announce the next generation
of Enterprise Computing for the AI ERA
with the IBM tm2 processor and a preview
of the IBM Spire accelerator both are
expected to be available in
2025 developed using Samsung 5 nanometer
technology the new IBM telm 2 processor
will feature eight high performance
cores running at 5.5 gz the processor
will include a 40% increase in onchip
Cache capacity and it will integrate a
new data processing unit specialized for
Io acceleration and the next generation
of onchip AI acceleration
we've also significantly enhanced the AI
accelerator on the telm 2 processor the
compute power of each accelerator is
expected to be improved by 4X reaching
24 trillion operations per second at the
same conference where we announced the
upcoming telm 2 processor IBM also
showcased the IBM Spire accelerator the
Spire accelerator will contain 32 AI
accelerator cores that will share a
similar architecture to the AI
accelerator integrated into the T 2 chip
both IBM telm 2 and the Spire
accelerator are designed to support a
broader larger set of models with what's
called Ensemble AI method use cases
using Ensemble AI leverages the strength
of multiple AI models to improve overall
performance and accuracy of a prediction
as compared to individual models to
learn more hit the link below thanks so
much for joining me today for this
episode of IBM Tech now if you're
interested in learning more about the
topics I've covered make sure you
explore the the links in the description
of this video and of course please don't
forget to subscribe to our channel to
stay up to date on what's going on at
Tech now
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